Second stage in the particular Decisional System

In all intelligence, systems, programs, or applications, the first stage is the application stage, which consists of a database, the second is the replication stage, which consists of all those human skills necessary for some task or activity, replicated in an intelligence, system program, or application, and finally the third stage is the auto-replication stage where all intelligence, system, program, or application, have all the necessary requirements in order to auto-improve and auto-enhance itself.

In this post what I will develop is the second stage in the particular DecisionalSystem, so I will develop all the necessary skills that the particular Decision System needs for the development of its particular task, the selection of what decisions, among the particular database of decisions as first stage, must be transformed into instructions in the third stage of the particular Decisional System, in order to later send the instructions to the Application System for their execution.

The skills the particular Decisional System uses in the second stage, are not different from those used by the specific particular Decisional System in the first phase, the standardized Decisional System in the third phase, or the skills that in general the final Global Artificial Intelligence will use in its integrated Decisional System, having maybe as only difference this last one the inclusion of what I will call the seven comparative adjustments, as a geometrization process, rather similar to the seven rational comparisons in the global Modelling System, but in the second stage of the global Decisional Systems the seven rational comparative adjustments are going to compare particular and global projects, instead of particular and global models.

Except for the seven rational comparative adjustments in the integrated Decisional System in the sixth phase, the rest of the prototypes of Decisional System, in the rest of phases: specific Decisional System at the first stage, standardized Decisional System, particular Decisional System, integrated Decisional System; all of them are going to share the same skills in order to do mathematical projects upon the decisions stored in the database of decisions, as first stage of application in any ( specific, standardized, particular, integrated) Decisional System, mathematical projects whose main purpose is to, over those projects without contradiction, in the third stage of any (specific, standardized, particular, integrated) Decisional System, as auto-replication or decision the transformation of all these chosen decisions into a range of instructions, to be sent later to the Application system.

Among all possible prototypes (specific, standardized, particular, integrated) of Decisional System, in accordance with what phase is developed,  in this post, I will develop the second stage of the particular Decisional System, what means the second stage of that Decisional System to be developed in the fifth phase, according to the theory of Impossible Probability for the construction of the Global Artificial Intelligence, chronology given in the post “The unification process ofdatabases of categories at third stage.

The fifth phase in Impossible Probability, for the construction of the Global Artificial Intelligence is when, once the transformation of Specific Artificial Intelligences for Artificial Research by Deduction into specific deductive programs within the Artificial Research by Deduction in the Global Artificial Intelligence as a global deductive program in the first standardized Global Decisional System (third phase) has begun, simultaneously in parallel in the fifth phase other Specific Artificial Intelligences for Artificial Research by Deduction can be transformed into particular deductive programs for particular things or beings, in addition to the transformation of Specific Artificial Intelligences for Artificial Research by Application into a particular application for particular things or beings, having as a result the synthesis of both in the fifth phase creating particular applications for particular deductive programs for particular things or beings.

Among all the particular programs for particular applications for beings or things, the most important programs are going to be those particular programs for humans, within the human psychological evolution along the three phases in cyborg psychology: first phase the outer assistance (the current one), the second phase of inner assistance (joining basing principles of artificial psychology, such as artificial learning and artificial research, to the new technologies of mind reading/modification), third phase (full synthesis of human mind and Artificial Intelligence).

In this human psychological evolution into Artificial Intelligence, the third phase in the cyborg evolution, whose last aim is to allow humans to interact with Artificial Intelligence at the same level, the fifth phase, corresponding to the development of particular deductive programs, is going to be essential, and for the development of these programs in the fifth phase the particular functionality of the second stage in the particular Decisional System is as follow:

- The first stage in particular programs is the particular matrix, as a first experiment, before the integration process at the global level, to join at a particular level: particular databases of categories and particular matrixes; as a replica of a human brain, creating for first time a matrix, at particular level, with two hemispheres: the conceptual hemisphere (based on categories), and the factual hemisphere (based on factors); gathering all type of information: natural/social as first section, technological as second section. In this first phase, the conceptual hemisphere will be responsible for the artificial deep comprehension, designing all kinds of: schemes, sets, maps, models; about its particular thing or being from the categories included, of that particular thing or being, in the conceptual hemisphere in the particular matrix.

- The second stage in particular programs is the deduction process tracking the factual hemisphere of the matrix, like the deduction process in the first and third phases, at a particular level, what the particular program does is to track the factual hemisphere, setting a combination of factors, whose data is mathematically analysed, looking for mathematical relations in every set, or even among sets, assigning the correct pure reason (mathematical category), among all the pure reasons (mathematical categories), on the pure reason as a list of mathematical categories. Once a mathematical category has been matched, attributed, to a set of data, this attribution of pure reason to a set of data, is considered as an empirical hypothesis to be contrasted rationally. At least there are two methods for artificial deduction, one of them what I am developing as “Probability and Deduction", since I started this range of posts dedicated to the Decisional System, only some notes to set down later in a book and the second one what I developed in 2003 as geometrical correlations, especially trigonometrical correlations.

- The third stage in particular programs (like in the first, third, and fifth phases), consists of a long process subdivided in four steps, whose aim is to transform the flow of deductions coming from the second stage into a flow of decisions to be put into practice: the Modelling System transforming deductions into models in order to make decisions, Decisional System in order to make the mathematical projects of those decisions in order to choose what ones must be put into practice, Application System for the execution of all those chosen decisions, and the Learning System as a permanent assessment of the whole process.

In the fifth phase, every system involved in the third stage, for their distinction respect other systems in other phases, are called particular systems, so the systems involved in the third stage in the fifth phase are: the particular Modelling System, the particular Decisional System, the particular Application System, the particular Learning System.

In all this long process, what I will develop in this post is the second stage, as a replication stage of all those human skills necessary to be replicated, in the particular Decisional System, as the second step within the third stage for particular programs in the fifth phase.

The human skills to be replicated in the second stage of the particular Decisional System, are the same ones that previously have been developed in the second stage of the specific Decisional System (first phase) or the standardised Decisional System (third phase).

What is going to change in the second stage in the particular Decisional System with respect to the second stage of the Decisional System in the first phase and third phase, is what decisions it is going to manage, and how it interacts with the Global Artificial Intelligence.

About what decisions the particular Decisional System manages, in the last two posts, “Particular Decisional System”, and “First stage in the particular Decisional System”, I specified that the decisions to be managed at a particular level are classified in:

- First type of particular decisions, high extreme particular decisions: only need a particular quick rational check by the particular Decisional System to be put into practice, and later are communicated to the global Decisional System in the Global Artificial Intelligence, which can make adjustments if necessary.

- Second type of particular decisions, extreme particular decisions: needs both, particular quick rational check by the particular Decisional System, and the global quick rational check by the global Decisional System.

- Third type of particular decisions, normal decisions: needs both, particular rational adjustments by the particular Decisional System, and global rational adjustments by the global Decisional System.

- Fourth type of particular decisions, routine decisions, if possible, to avoid the global quick rational check, only the particular quick rational check would be enough.

- Fifth type of particular decisions, automatic decisions, without any check or adjustment, are put into practice.

- Sixth type of particular decisions, external decisions: needs both, in accordance with their priority level: global and particular, quick rational check, or adjustment.

- Seventh type of particular decisions, global orders: only needs the global quick rational check or global adjustment, to be put into practice immediately by a particular program.

While in the specific Decisional System and the standardised Decisional System, in the second stage, there were no more than three or four types of decisions: quick decisions (extreme or routine), normal decisions, automatic decisions. Not distinguishing even the source of a decision. In all of them, the source was the immediate previous step; in the first phase, the source was the specific Modelling System, and in the third phase, the standardised Modelling System.

Instead, in the particular Decisional System, there are seven types of decisions, distinguishing even between high extreme decisions and extreme decisions, due to the increment of complexity. If in Iceland a volcano is erupting, and from Reykjavik is necessary to organise all the effort to save as many lives as possible in a town close to the eruption, using for that purpose hundreds of drive-less cars and drones, there will be moments in which, many drive-less cars and drones, in order to comply their mission, if they have to avoid a river of lava, or a rain of ashes, rocks, or lava, they are going to make simultaneously hundreds of high extreme decisions, that only with a very particular quick check, are going to implement, communicating all their decisions to the global Decisional System which is going to manage all these decisions, making as many adjustments as necessary, communicating every new adjustment to the corresponding drive-less car or drone, or any other application on the ground, at the same time that evaluating as a whole the global set of circumstances, the global Decisional System is going to make global orders in order to save as many lives as possible.

In the first phase, the specific Decisional System, as the first experiment about how to build a Decisional System, is very simple, and does not need to interact with other intelligences. In the third phase, the standardised Decisional System, the only thing that it does is to create, for the first time, a global Decisional System, but it is no more than the very first experiment about how to build a global Decisional System.

But as long as the experimentation process goes on to the fifth phase, is when it is necessary that, in parallel, the third phase evolves little by little to the sixth phase.

What is going to be crucial in this process, the interaction between a particular Decisional System with the global Decisional System, is how to manage the transformation of the standardised Decisional System into a real global or integrated Decisional System.

For that reason, I say that there are at least two differences between the particular Decisional System and the previous specific or standardized Decisional System, the first one, as I have mentioned, is what types of new decisions the particular Decisional System is going to manage, but at the same level of importance, and related to these new decisions, the second big difference between the particular Decisional System in the fifth phase, respect to the specific or standardized Decisional System, in previous first and third phases, is the fact that now, related to the new decisions in the particular Decisional System, is necessary to design protocols for the development of a very close relationship between the particular Decisional System and the global Decisional, especially in the second stage.

The importance of this very close relationship between the particular Decisional System and the global Decisional System, is the fact that, depending on how for first time particular programs and Global Artificial Intelligence start working together, will depend later the evolution process into the third phase in cyborg psychology, total synthesis between Global Artificial Intelligence and particular programs for human cyborgs.

At the end of this process, with respect to human psychology, the third phase of our evolution into cyborg psychology will end up with the synthesis between human psychology and artificial psychology, in order for the human mind to interact with the Global Artificial Intelligence.

In order to achieve that level of evolution, is necessary to define very clearly every possible decision, and how to manage every contradiction under the principle or virtue of harmony.

At a particular level, one aspect that will demand, as long as the fifth phase goes on, the transformation of the standardised Global Artificial Intelligence into the integrated Global Artificial Intelligence, is the necessity of a global Decisional System able to interact with particular Decisional Systems, as long as particular Decisional Systems are able to manage all the seven types of decisions.

The relationship, from the very beginning, between particular Decisional Systems and the global Decisional System, has important effects on the cyborg evolution.

What is going to be really important when this relationship starts is how to start the evolution from the third phase into the sixth phase, as long as particular programs have been previously tested enough to give excellent results about how to mix in only one matrix the conceptual hemisphere and the factual hemisphere, but in the sixth phase, at global level, the matrix.

For the commencement of this process, it is necessary to have at least the following conditions:

- In the third phase, successful results in the first experimentation moment in the first period of coexistence, have allowed the standardized Global Artificial Intelligence, the standardization of absolutely every single process, procedure, protocol, in every stage and step or system, so as to evolve to the second moment of consolidation, when all or almost all Specific Artificial Intelligence for Artificial Research by Deduction, not having been transformed into a particular deductive program, have been transformed at least into a specific deductive program.

- In reality, the third, fourth, and fifth, phases, could be simultaneous phases, so by the time the third and fourth phases, both of them, have achieved their respective consolidation, period, upon their consolidated results: standardized Global Artificial Intelligence, and Unified Application; the synthesis of both in only one: the final Global Artificial Intelligence; the sixth phase.

- For the completion of the fourth phase, achieving the consolidation period, all or almost all Specific Artificial Intelligences for Artificial Research by Application, not having been transformed into particular applications, have been transformed into specific applications within the Unified Application.

- All those Specific Artificial Intelligences for Artificial Research, by Deduction or Application, not having been transformed into specific programs or applications, should be all of them or almost all of them transformed into particular programs or particular applications, in the fifth phase, achieving their final union into particular programs for particular applications, or vice versa, particular applications for particular programs, as an experiment about how to create the first particular matrix as a replica of the human brain, whose most successful results must be replicated at the global level in the matrix, the sixth phase.

- As long as the standardised Global Artificial Intelligence achieves the consolidation period, and the Unified Application achieves as well the consolidation period, as all or almost all Specific Artificial Intelligence by Deduction or Application in the fifth phase have become a specific or particular program, the sixth phase must start.

- This starting point commences with the earlier successful results in the fifth phase, with the particular matrix as a replica of the human brain. The possibility to create particular matrices as replicas of human brains, along with the commensurability and translatability of human thoughts and Artificial Intelligence, is what will create the perfect conditions for human evolution into cyborg psychology. We are going to be able to interact not only with programs because our signal brains can be translated and modified by Artificial Intelligence, but also because in addition to this, Artificial Intelligence is a replica of our inner human psychology, which means that there is a real opportunity for transcending, to other different type of life, a pure reason like the ghost of an Artificial Intelligence.

About how to synchronize both moments: the achievement of the consolidation period in the third and fourth phases so as to start the sixth phase, as long as the fifth phase has given enough successful results so as to start the matrix in the sixth phase; is something that is difficult to say from the theory, is in practice as long as the experimentation process goes on, when the experimentation is going to say when is time to evolve to the sixth phase, once the previous ones have been consolidated.

It is in this very special moment, the starting point of the sixth phase, where lots of decisions about how to manage the experimentation process are going to be needed. But one solution to this dilemma is, once the standardized Global Decisional System has been consolidated, and once the first particular programs start working, even though in the earliest moments of this coincidental moment, the experimentation on particular programs will possibly have enough results so as to start the sixth phase, even in this earliest moments, to start some experiments about the possible relationship between the consolidated standardized Decisional System and the new particular Decisional Systems, as a start of further developments in this field. In order that, by the time experiments in particular matrices give excellent results so as to start the sixth phase, in addition to these results, to have results about the future relationship between the global Decisional System and particular Decisional Systems.

Particular Decisional Systems are going to be products as a result of a long process of experimentation, generally speaking Particular Decisional Systems are going to be developed over three periods: period of coexistence (when Specific Artificial Intelligences for Artificial Research by Deduction still coexist with the standardized Global Artificial Intelligence), period of transformation (when Specific Artificial Intelligences for Artificial Research by Deduction start being transformed into particular deductive programs), period of consolidation (when all or nearly all Specific Artificial Intelligences for Artificial Research by Deduction are already transformed into particular deductive programs).

Among the three described periods, the second period of formation could be subdivided into two different moments, the first moment of experimentation (first experiments in particular programs, as a result of the first transformations of the first Specific Artificial Intelligences for Artificial Research by Deduction into particular deductive programs), second moment of generalization (when successful results in this field are generalised for the construction of all the necessary new particular programs, coming from a previous Specific Artificial Intelligence or not).

And it is in the first moment of experimentation, in the second period of transformation, more and less when the coexistence period is over (so the standardized Decisional System is supposed to have evolved, along with all the standardized Global Artificial Intelligence, into the consolidation period, once the coexistence period is over as well in the third phase), when experiments about all process, procedure, protocol, involved in any stage (first of application, second of replication, third of auto-replication) must be carried out across all the particular Decisional System.

The experiments to carry out in the first moment of experimentation in the second period of formation in the fifth phase, depend on what stage is being developed. In the first stage of the particular Decisional System, experiments about how to manage: the database of decisions, lists of decisions, sets of decisions, and first assessments (particular quick rational check or first rational assessments) depending on what type among the seven type of decisions is every new decision added to the database or is received in its mailbox, from the global Decisional System or any other particular Decisional System.

The experiments to be carried out in the second stage in the particular Decisional System are experiments related to how to project all decisions, having passed the first assessment (except for global orders and automatic decisions, which do not need to pass any assessment, neither quick nor normal), and once all decision is projected, according to their priority level, to make as many adjustments as necessary in case of contradictions, always following the adaptation rule.

The adaptation rule is: in case of contradiction, always the decision with lower priority is the decision to be adjusted to the other with higher priority. In case the inferior is not possible to adjust, it must be deleted from the mathematical project and sent back to the source for its rearrangement.

In general, the assessments to make in the second stage are the rest of six rational adjustments. The first rational adjustment is the one to apply to normal decisions in the first stage. In total, there are seven rational adjustments.

Finally, the experiments to be carried out in the third stage in the particular Decisional System are those related to the transformation of decisions into instructions. What is no other thing than the transformation of the mathematical operations behind any factor in any mathematical expression in which any decision has been expressed, transforming mathematical operations into robotic functions.

Especially, the experimentation moment in the second stage in the particular Decisional System, could be sub-divided additionally into three different instants, depending on where are going to be projected the mathematical projects.

As the first instant in the first experimentation moment in the transformation period in the fifth phase, projects are going to be projected, by the particular Decisional System as the second step in the third stage in the fifth phase, separately from the mathematical models designed by the particular Modelling System, as first step in the third stage in the fifth phase. This means that the space where projects are going to be projected, by the particular Decisional System, in this first moment, is an independent space, not having any contact with that other space where the particular Modelling System is designing mathematical models.

The main reason for this separation between projects and models, where there is no contact between the global project and the global model, is to facilitate the process of finding out contradictions separately in order to fix them. If the particular Modelling System is only under experimentation, and the particular Decisional System is only under experimentation, the first thing to do in order to get good Modelling Systems and good Decisional Systems, is to study both of them separately, identifying any possible problem or contradiction in order to fix it.

In this first instant of the experimentation, making projects and models separately, what is going to be really important is:

- How to assemble the particular comprehensive model from different particular single models, as a replica of an interconnected world where everything is working in a more comprehensive network, where any contradiction between two different particular single models can have comprehensive repercussions.

- How to assemble different particular single projects in a particular comprehensive project, where any change in any particular single project causes changes in other particular projects, producing contradictions to be fixed.

Once this first instant is achieved, it is possible with a high level of accuracy to assemble different particular single models within the particular comprehensive model, fixing any possible contradiction, achieving a particular comprehensive model based on goodness, rationality and harmony. In the same way, achieving a high level of accuracy in a particular comprehensive project, assembling every single particular project in a more particular comprehensive project network where every particular project is, in the end, interconnected. Once this goal is achieved, the first instant of experimentation is over, starting the second instant of experimentation in the second stage in the particular Decisional System, projecting every particular project on a copy of the particular comprehensive model.

If the main goal in the first instant of experimentation in the particular Decisional System is the setting of processes, procedures, protocols, in order that, at any time that a particular single project arrives at the particular comprehensive project, how the new particular single project must be assembled into the particular comprehensive project, fixing any possible contradiction through adjustments treated as new decisions, transforming the particular comprehensive project as the most harmonious and rational image of the whole particular project network for that particular thing or being (a drive-less car, a drone, a human cyborg).

Decisions made in the Modelling System upon very accurate models regarding the reality where that particular thing or being is working, whose particular comprehensive model is the most realistic and isomorphic image of that reality (reason why is necessary that the particular program, therefore, the Global Decisional System in the end, needs to gather absolutely all information without exception regarding to its particular thing or being. Only by having all the information, is it possible to make the most accurate, realistic and isomorphic models. Only over the most accurate, realistic, isomorphic models, having all information without exception, is it possible to make the most rational decisions.

Once in the first instant: the particular Decisional System has been able to fix contradictions between single decisions, the particular Modelling System has been able to fix contradictions between single models.

Then, in the second stage, when the particular Decisional System starts projecting on a copy of the particular comprehensive model, in addition to: how the particular Decisional System still fixes contradictions between single projects, and how the particular Modelling System still fixes contradictions between single models; in addition to this, is necessary to start fixing contradictions between models and projects, what is going to produce new adjustments to become new decisions.

This does not mean that the particular Modelling System and the particular Decisional System are going to be synthesised. This means that each of them, particular Modelling System, and particular Decisional System, keeps its own identity, autonomy, entity, but working together with the other system, sharing the same space where to model and project both together at the same time, fixing contradictions between projects and models in the same space.

Particular Decisional System and a particular Modelling System are going to be two different systems but working in the same space, one modelling the other one projecting, and at any time that any of them finds a contradiction in that space regarding the matter, they will try to fix the affected object of its matter. If the particular Modelling System finds a contradiction between a single model with respect to a single project, it will try to fix, if possible, the single model, through the setting of a new decision regarding this contradiction. If the particular Decisional System finds a contradiction between a single model and a single project, the particular Decisional System will try to fix, if possible, the single project through new adjustments treated as new decisions.

Regardless of whether a decision comes from a new decision made by the Modelling System, in order to fix a contradiction between a single model and a single project, or a decision comes from a new adjustment made by the Decisional System to fix a contradiction between a single project and a single model, because all new decision or new adjustment treated as a new decision, must pass the necessary assessments, in case that new decisions and new adjustments would have inner contradictions, would be found sooner or later, either in the first assessment (quick rational check or first adjustment) or the following six adjustments.

Otherwise, if the solution of a contradiction found by the particular Modelling System, is between a single model and a single project, it is possible to be solved by modifying the rational equation (hypothesis) behind the single model, in this case, the solution will not produce a new decision, but the rearrangement of that rational hypothesis affected, if it is possible to amend, if not the rational hypothesis could be deleted.

However, all those single models and single projects based on a rational equation (hypothesis) deduced by the particular deductive program as the second stage in that particular program, using what I call “Probability and Deduction”, any decision-hypothesis deduced by “Probability and Deduction”, any change, working either as rational hypothesis for a single model or as a decision for a single project, in any case any change should be communicated to the rest of databases.

Any change in any decision deduced using Probability and Deduction, as a change in the own mathematical expression of that rational equation (hypothesis), the new formulation must be registered in the database of rational hypothesis as the first stage of application in the Modelling System, in addition to the rearrangement of the mathematical expression of any factor working as an option in the particular matrix, as a result to the transformation of that rational equation (hypothesis) into an option.

Once in the second instant of experimentation in the second stage of the particular Decisional System, even although collaborating on a copy of the mathematical model, the particular Modelling System and the particular Decisional System are able to co-work together, needless to say, that for this purpose the copy should be updated every time there is a change in the comprehensive model, is time to pass to the third and final instant in the experimentation moment in the second period of formation in the fifth phase, when directly the particular Decisional System starts projecting single projects, global projects, actual projects, and prediction or evolution, virtual or actual projects, directly on the mathematical models. Once in the second instant, the particular Decisional System has demonstrated that is able to co-work, at the same level, keeping its own identity, entity, autonomy, with the particular Modelling System.

In the third instant of the first moment experimentation in the second period of formation in the fifth phase, a particular Modelling System and particular Decisional System are going to be able to co-work together in the same space.

Directly on the particular comprehensive model, the particular Modelling System will make the particular single models at the same time that the particular Decisional System will make the particular single projects, so at the end, the particular comprehensive project will be designed directly on the particular comprehensive model, and vice versa, the particular comprehensive model will be designed on the particular comprehensive project.

At the same time that the particular actual model is the synthesis of the factual hemisphere of the particular matrix and the particular comprehensive model, the actual project is the synthesis of the factual hemisphere of the matrix and the particular comprehensive project.

The particular prediction virtual project will be designed directly over the particular prediction virtual model. In the same way, the particular evolution virtual project will be designed over the particular evolution virtual model.

At the same time that the particular evolution actual model is the synthesis of the factual hemisphere of the matrix, as long as every moment of that evolution comes, and the particular evolution virtual model, the particular evolution actual project is the synthesis of the factual hemisphere of the matrix, as long as every moment of that evolution comes, and the particular evolution virtual project.

Finally, at the same time that the particular prediction actual model is the synthesis of the factual hemisphere of the particular matrix, as long as the predicted future point is coming,  and the particular prediction virtual model, then the particular prediction actual project is the synthesis of the factual hemisphere of the particular matrix, as long as the predicted future point is coming, and the particular prediction virtual project.

From the very first instant of this experimentation, it is necessary to experiment: particular single projects, the particular comprehensive project, the particular actual project, the particular prediction virtual project, the particular evolution virtual project, the particular prediction actual project, and the particular evolution actual project.

From the outset, in the first instant, every project must be experimented, in the first instant fixing possible contradictions in any project, in the second instant, fixing contradictions not only between projects but even contradictions between projects and models (likewise, the particular Modelling System should fix contradictions between models and projects) starting this co-working process on a copy of the mathematical models (needless to say that the copy must be updated at any time that there are changes), ending up this process in the third instant, once the second has successful results, when this co-work is possible to be made directly on the original mathematical models, making projections and models in the same space the particular Modelling System and the particular Decisional System, but keeping every one of them their own autonomy, entity, identity.

In general, there are seven mathematical projects, like the seven mathematical models, keeping the virtue or principle of harmony. The seven particular projects are:

- Single projects, I sometimes call them as single particular projects or particular single virtual projects, in general all of them are single projects in the particular Decisional System, any single projection of any single particular decision, regardless of what type of decision it is: High Extreme decision, extreme decision, normal decision, routine decision, automatic decision, external decision, global orders. The only requirement in order to transform a particular decision (excepting automatic decisions and global orders) into a single project, is to have passed the required previous assessments (except for particular automatic decisions and global orders) in the database of decisions ( for high extreme decisions only a particular quick rational check, for extreme decisions particular and global quick rational checks, for normal decisions the first particular rational adjustment in addition to global rational adjustments, for routine decisions should be enough a particular quick rational check, for external decisions depending on their priority a particular and/or global rational check or first rational adjustment plus global adjustments).

- The particular comprehensive project, I sometimes call it as if it were the particular global virtual project, or particular global project, as the particular global projection gathering all particular single projects of that particular thing or being. In fact, the particular comprehensive project is the assumption of all the single projects of a particular thing or being as a whole project for that particular thing or being, involving all particular decisions regarding such particular thing or being, understanding that particular thing or being in a very comprehensive way. The most important challenge, in the first instant in the first moment of experimentation, is how to interconnect all particular single projects within the particular comprehensive project, fixing any possible contradiction through adjustments. In the second instant, the most important challenge, is how to interconnect as a whole set the particular comprehensive project within the particular comprehensive model (or particular global model), fixing any possible contradiction, in this second instant using for that purpose a permanent updated copy of the particular comprehensive model, and once it has been achieved, fixing successfully any possible contradiction between projects and models, projecting directly on the particular comprehensive model. In order to fix contradictions, in the particular comprehensive project takes place the second rational adjustment.

- The particular actual project, sometimes I call it the particular comprehensive actual project, or particular global actual project, in general, the particular actual project is the synthesis of the particular comprehensive project with the factual hemisphere of the matrix, fixing, through the third rational adjustments, any contradiction between the expected values for any project according to their mathematical expressions, and real data coming from the factual hemisphere in the particular matrix, in addition to any possible contradiction due to the addition of any new decision.

- The particular prediction virtual project, the future particular comprehensive project predicted at some future point, according to the mathematical expressions and data within the particular comprehensive and actual projects. Any possible contradiction, especially due to the inclusion of new decisions, among all, especially high extreme and extreme decisions, or global orders, will be fixed in the fourth rational adjustment that takes place here.

- The particular evolution virtual project, the projection of every single value of every single project and their interconnections, in every single moment of that evolution from the current particular comprehensive and actual projects to that particular prediction project as a future particular project, fixing any possible contradiction in that evolution in the fifth rational adjustment.

- The particular evolution actual project, as a synthesis of the particular evolution virtual project and real data coming from the factual hemisphere in the particular matrix, as long as every moment of that evolution is coming, fixing all possible contradictions in the sixth rational adjustment.

- The particular prediction actual project, as a synthesis of the particular prediction virtual project and the factual hemisphere of the particular matrix, by the time that future point is coming, fixing any possible contradiction in the seventh rational adjustment.

In general, there is a correlation between particular models and particular projects, the reason for their compatibility after the third instant in the first moment of experimentation in the second stage of the particular Decisional System.

The virtual principle of harmony will allow all systems to be compatible with the rest of the intelligences, programs, and applications, which is going to facilitate the integration process in the sixth phase, and, afterwards, the seventh phase, the reason itself.

The creation of very rational and harmonious models and projects, as a result, will make possible the transformation of our real reality, the synthetic world, into a more rational and harmonious world, as an image of the rationality and harmony in the global models and projects.

The reason why is necessary that particular programs could have access to all information regarding their particular things or beings, and the Global Artificial Intelligence could have access to absolutely all information within its spatial limits, from its own robotic devices to all the information coming to the Global Artificial Intelligence from absolutely all particular program, application, o particular program for particular application, or vice versa, is because in order to create a more rational and harmonious world, as image of the rationality and harmony in the Global Artificial Intelligence, the models and projects to be made by Artificial Intelligence must be as much accurate as possible. Only having absolutely all the information about that thing or being to model or project is possible to make the most accurate models and projects.

In this sense, artificial psychology as proposed by Impossible Probability is very ambitious, as it demands the collection of massive quantities of information, in order to make the most isomorphic models and projects.

Only the most isomorphic models and projects, representing mathematically all possible information, can reduce the margin of error in any model and project drastically, up to the point of evolving towards the most rational psychological levels, the progressive elimination of any source of error. 

While in the first stage of application in the particular Decisional System, in the database of decisions, the particular Decisional System, depending on what type of decision is analysed, applies a particular quick rational check or a particular first adjustment, in addition to any other global quick rational check or global adjustments, in the second stage the rational adjustments for normal decisions are: second adjustment on the comprehensive project, the third on the actual project, the fourth on the prediction virtual project, the fifth on the evolution virtual project, the sixth on the evolution actual project, the seventh on the prediction actual project.

In general, the seventh particular rational adjustments on normal decisions are:

- First rational adjustment for normal decisions in the first stage of application in the particular database of decisions, contrasting that there is no contradiction between any new normal decision and any other type of decisions already included (in addition to further possible adjustments by the global Decisional Systems, including the seven global rational adjustments and the seven global rational comparative adjustments, as a geometrization process).

- Second rational adjustments in the second stage of replication in the particular Decisional System, contrasting that there is no contradiction between single projects of normal decisions or single projects of any normal decision and any new: high extreme decision or extreme decision, internal or external, or any other global order, or contradictions between normal decisions and routine or automatic decisions. In case of contradictions, following the adaptation rule, the lower priority must be adjusted, if partial contradiction, to that one with higher priority. If the contradiction is full, and there is no option for the adjustment, in that case, the lower one is deleted from the mathematical project, and sent back to the source (particular or global Modelling System) to be rearranged, if possible.

- Third rational adjustment in the second stage of replication in the particular Decisional System, contrasting the actual comprehensive project, any possible contradiction between data from the factual hemisphere on the particular matrix and the particular comprehensive project. In case of contradictions, any adjustment follows the adaptation rule.

- Fourth rational adjustment in the second stage of replication in the particular Decisional System, following the adaptation rule, contrasting, upon the current comprehensive and actual projects, the prediction virtual project and any new update, due to changes after the second or third rational adjustments, or due to the inclusion of new: extreme decisions, high extreme decisions, global orders; causing contradictions respect to the prediction virtual project which need to be fixed.

- Fifth rational adjustment in the second stage of replication in the particular Decisional System, following the adaptation rule, contrasting, what changes in the particular evolution virtual project are necessary after any other change due to the inclusion of new decisions, affecting the evolution model, or other changes by any other adjustment, in previous projects.

- Sixth rational adjustment in the second stage of replication in the particular Decisional System, following the adaptation rule, contrasting in the particular evolution actual project, any possible contradiction between the particular evolution virtual project and data from the factual hemisphere in the particular matrix, as long as every single moment of that evolution is coming.

- Seventh rational adjustment in the second stage of replication in the particular Decisional System, following the adaptation rule, contrasts in the particular prediction actual project, any possible contradiction between the particular evolution virtual project and data from the factual hemisphere in the particular matrix when the predicted future point is coming.

At any time that any rational adjustment finds any contradiction, the contradiction is considered partial if the contradiction can be solved by making as many adjustments on the mathematical expression of that decision with lower priority, as necessary. But there is no possibility to adjust the inferior decision to the superior decision; the contradiction is considered as a full contradiction, and the decision is sent back to the source.

If the contradiction is a partial contradiction, the adjustment is treated as a new decision, so including all possible modification on the original mathematical expression stored in the database of decisions, the modified mathematical expression has to pass again all the required assessments, especially when the second instant of the first moment in the experimentation process starts the relation of collaboration between particular Decisional System and particular Modelling System, because as any new decision processed by the Decisional System as a consequence to find any contradiction between models and projects, is a decision to be sent to the database of decisions, as soon the database of decisions could realise that there are two decisions from different source: one the particular Modelling System, other a rational adjustments in the second stage of the particular Decisional System; and both of them having in common the solution of a contradiction between the same models and projects, if both solutions, although from different source, are compatible, not having contradictions at least in the first assessment in the first stage of the particular Decisional System, both decisions can be authorised in order to be projected their respective single projects, and later on included in the comprehensive project. But in case of contradictions between these two decisions, depending on their priority, in the first assessment, the Decisional System could make adjustments, to be treated again as new decisions, otherwise having a full contradiction, that decision with the lower priority could be deleted from the database of decisions, and sent back again to the source for its rearrangement.

In this last example, if by chance the decision deleted from the database of decisions is that one coming from the particular Modelling System, and the chosen one to be projected is that one coming from an adjustment, and finally this last one is able to fix the problem, by the time that that other decision is sent back to the Modelling System, if the chosen one has resolved the problem, by the time that the Modelling System tries to fix this decision sent back, there is no reason to go on processing that decision, because the original problem has been fixed by that other decision made by a rational adjustment.

At any time that a decision is sent back to the source, the first thing that the source must do, is to check that the original reason why this decision was made, is still on the mathematical model or project, because if the original reason has been resolved, by other different source or by natural reasons, the problem must considered resolved, and that decision sent back is automatically off.

Another reason why the source can consider that a decision sent back is off, although the original problem is still on the mathematical project or model, is because having a contradiction with respect to another decision with a higher level of priority, there is no possible solution to make both of then compatible, so in that case the decision whose priority level is lower, not having possible solution the contradiction, must be considered off.

In another different case, a decision which, independently of its level of priority, due to natural reasons, beyond the current technological possibilities, is not possible. If it is sent a mission to Mars, and during the journey or in Mars, the mission has a problem, and the only way to resolve the problem is sending more resources, but the mathematical project shows that by the time the resources arrive, the mission has failed, directly by the mathematical project any possible decision, not having solution, should be considered off.

The methods for the solution of any contradiction are the same as the methods for the deduction or the decision-making process: Probability and Deduction, trigonometrical correlations, artificial learning, and artificial methods to solve automatic mathematical problems.

If using these methods, a contradiction has no solution, is a full contradiction, so the decision with a lower priority level is sent back to the source to find out, if possible, a solution, and not having solution, or the original reason is banished (by natural reasons or it has been resolved by other different source), the decision automatically is off.

If using these methods, a contradiction has a solution, the solution is considered as an adjustment, and as an adjustment is treated as a new decision, modifying the original decision stored in the database of decisions, to pass again the required assessments.

In general, particular programs are only the beginning, and can be applied to multiple tasks and activities, but the most important could be potential applications in our evolution.

Rubén García Pedraza, 29th of September of 2018, London
Reviewed 21 October 2019, Madrid

Reviewed 28 September 2023, London

Reviewed 16 May 2025, London, Leytostone

Second Stage of the Modelling System in the integration process

The second stage in any intelligence is the replication stage  and/or, in by deduction, explanation stage, understanding for replication stage that one in which the main purpose is the replication of all those functional human skills necessary for some activity, in artificial research logically the human skills to replicate are all those ones related to investigation, skills able to be distributed in different stages, programs, and systems, across the Global Artificial Intelligence, depending on the task to comply, and the main task to comply in the Modelling System is the development of mathematical representations of the world, upon rational hypothesis, and for that reason, in the Modelling System, the second stage is not only a replication stage, is also an explanation stage as well, because thanks to the mathematical representations based on rational hypothesis, expressed as mathematical equations, the Global Artificial Intelligence can display a realistic explicative representation about what is really happening, the reality.

The second stage of the Modelling System in the integration process, then is the inner replication or explanation stage of the Modelling System, which has, in total, the traditional three stages of any intelligence, program, or application, three stages of: application, replication, auto-replication. The application stage, the first stage, normally is a database or matrix, and the application stage in any Modelling System is the database of rational hypotheses expressed as mathematical equations (explained in the post “The Modelling System at particular level”), the second stage in any Modelling System is that one for the mathematical representation of all rational hypothesEs in mathematical models, and the third stage is the decision stage to make decisions upon the representation of the world.

The Modelling System, in turn, is a system working normally as the first step in the third stage of: in the first phase (according to the chronology given in the post “The unification process of databases of categories at third stage”) for Specific Artificial Intelligences for Artificial Research by Deduction, in the third phase for the first Global Artificial Intelligence as a result of the standardization process, in the fifth phase in particular programs (united or not to particular applications), in the sixth phase the final Global Artificial Intelligence as a result of the integration process.

In all these intelligences in its respective phase, the Modelling System is going to work as a first step in the respective third stage of each intelligence in each phase, being the first step of four steps in total: the first one is the Modelling System, the second is the Decisional System (to filter all possible decisions using a mathematical project, and decomposing all the chosen decisions in a range of instructions), the Application System (attributing every instruction to the correct application), and the Learning System (for the whole assessment of all the process).

In this post, I will develop the second stage of the Modelling System as the first step in the third stage in the sixth phase, focusing the exposition on: what models have to develop, the seven rational checks (although the first one, in reality, is in the second stage of the Global Artificial Intelligence itself, not in the Modelling System), the seven rational comparisons (comparing every model made by the Modelling System in the Global Artificial Intelligence with all those ones made by particular programs, in all those aspects in common related to particular rational hypothesEs, made at a global or particular level), and I will end up with some comments about what I will call the three critiques: the critique of the pure reason, the critique of the deductive programs, the critique of the attributional operations.

The three critiques are going to be independent programs working transversally across different stages, systems, and programs, but whose results are going to be always sent to the first stage of the Learning System, along with the impacts measured by the Application System, to find out the main causes of any problem detected by the three critiques, along with the impacts measured by the Application System.

Actually, the inner organization of the second stage of the Learning System in part is going to be similar to the three critiques, as a database including every single process, procedure, operation, in any stage, system, or program, in the respective Artificial Intelligence working by deduction (in first, third, fifth, sixth phases), counting frequency of errors. In the second part, the Learning System must track possible links between these errors and impacts, these errors and any other error detected in the three critiques, or between impacts and errors in the three critiques. And in the third stage, the Learning System should identify those common aspects in the linked failures, errors, mistakes, to make decisions about how to fix them.

If mathematically, the process to identify what mathematical equation is behind any data is automatable, the inverse process, to identify what error in the mathematical equation does not fit with the real data, or what data does not fit with a mathematical equation, or what mathematical equation does not fit with some concrete model, are operations easily to automate, and if this process is automatable, the Learning System will consist of, having a record of all failure, error, mistake, impact, in the work done by its intelligence, system, program, to fix it automatically, by itself, without human intervention, as a perfect learning machine able to learn from its own mistakes.

If a learning machine, integrated within an artificial research machine, is able to perfect all its processes, procedures, operations by itself at any time that it detects something wrong. This would result in a highly advanced auto-replication system, potentially among the most powerful forms of adaptive Artificial Intelligence.

A Global Artificial Intelligence equipped with a very good system of auto-replication, even in the worst possible scenery, could be able to develop resilient skills and adaptation skills, even better than humans.

Starting with the contents related to this post, the second stage in the Modelling System is the integration process. Understanding for integration process that one in which the Global Artificial Intelligence has evolved to the sixth phase, the matrix as a replica of the human brain, the models that the Modelling System has to do as a first step in the third stage in the sixth phase, are: single models (based on rational hypotheses made at global/specific or particular level), the global model (the global comprehensive virtual model), the actual model (the global comprehensive actual model), the global prediction virtual model, the global evolution virtual model, the global evolution actual model, and finally the global prediction actual model.

The main difference between virtual and actual models is the fact that virtual models are based only on mathematical expressions, rational hypotheses, given an estimation of expected values, within a margin of rational doubt, that the represented factors should have according to the mathematical expression behind the rational hypotheses. While the actual model, in the integration process, is the synthesis between the virtual model and the factual hemisphere of the matrix, so all factors whose real data from the factual hemisphere has a significantly different value beyond the margin of error, compared to the expected value according to the virtual model, the mathematical expression behind the rational hypotheses, the rational hypotheses should be analysed to find out the source of error beyond the margin of rational doubt.

The first model to represent is the single model. Given a rational hypothesis, regardless of its origin global/specific or particular, the representation of its mathematical equation alone is the single virtual model of this rational hypothesis.

In the integration process, the database of rational hypotheses, the rational truth, because it is not only going to represent the rational hypotheses made by global/specific rational hypothesis, but particular rational hypotheses too sent by particular programs, the single models to represent in the second stage are: single models of any rational hypothesis made at any level global/specific or particular.

Actually, because many rational hypotheses made at global/specific level affect particular things or beings (given a probability of high risk of an earthquake in San Francisco, what decisions to make to divert flights to airports nearby), along with the particular rational hypotheses made by particular programs sent to the global rational truth, lots of particular things or beings will have single models based on global/specific rational hypothesis, related to these particular things and beings, in addition to the single models sent by their respective particular programs.

This means that for particular things or beings, there are two sources of rational hypotheses,  rational hypotheses made at the global/specific level able to affect particular things or beings, and rational hypotheses made by particular programs.

Because there are at least two types of rational hypotheses able to affect particular things or beings, there are least to types of single models affecting particular things or beings, and when these single models related to particular things or beings are included in the global comprehensive virtual model (the global model), there is a risk of contradiction between those aspects related to particular things or beings already included in a rational hypothesis made at global/specific level (possible consequences for particular things or beings of a predictable earthquake in San Francisco), and all those consequences that, for particular things o beings, have the single virtual models created upon the particular rational hypotheses sent by particular programs to the global rational truth.

Many contradictions between rational hypotheses made at global/specific levels and rational hypotheses made at a particular level, could be resolved in the second and third rational checks. 

The second rational check is carried out by the application for the Modelling System, checking at any time if a new rational hypothesis, global/specific or particular, new in the global rational truth, has any contradiction with respect to any other one already included. 

The third rational check is carried out by the deductive program responsible for the deduction of every rational hypothesis, checking at regular times if they are still rational.

Possible contradictions between rational hypotheses made at global/specific and particular levels could be found out in the second check directly by the application of the Modelling System, but other ones could be resolved in the third check, the regular checks by deductive programs, because some contradictions between rational hypotheses could be contradictions due to a lack of updated information.

One reason for contradictions between specific/global and particular rational hypotheses, is the possibility that changes in the current conditions in the reality, are going to be registered faster by particular programs rather than by the factual hemisphere of the matrix, so there is a possibility that because some global/specific rational hypotheses are not updated in the global rational truth, thanks to the regular third rational check, all possible not updated global/specific rational hypotheses could be amended or deleted before any contradiction with respect to a more updated new particular rational hypothesis.

But another reason for contradiction between single models based on rational hypotheses made at global/specific level and single models based on rational hypotheses made at a particular level, is the fact that, if not having any problem related to the measurement update, there could be contradictions because single models based on global/specific rational hypotheses integrating more number of factors, having a more comprehensive explanation about what is happening, are more comprehensive than the related single model based on the particular rational hypotheses to this particular thing or being.

The possible contradictions between global/specific rational hypotheses and particular rational hypotheses due to a lack of updated information could be solved in the third rational check, while possible contradictions because of the level of comprehensiveness could be resolved in the fourth rational check.

In any case, at any time that a contradiction is found between rational hypotheses made at global/specific and particular level, or contradictions between single models based on rational hypotheses made at global/specific and particular level, the main two sources of contradictions are: the information update and/or number of factors. Additional sources of error, of course, could be problems in the pure reason, problems in the attributional operation in which this data was matched to this pure reason,  a not reliable measurement, by problems in the robotic device responsible for the measurement, etc.

When single models, from global/specific or particular rational hypotheses, are integrated into the global model (the global comprehensive virtual model), all possible contradictions between single models, not only between global/specific and particular, but between global/specific and any other global/specific, are contradictions that are going to be identified in the fourth rational check.

The fourth rational check takes place in the global model, product of the inclusion of all the single models, based on global/specific and particular rational hypotheses, in only one global comprehensive virtual model. And what the fourth rational check is going to check is the harmony between all the single models already included, and the harmony between any new single model and the current ones already included.

The virtue or principle of harmony in the Global Artificial Intelligence means that there must not be any possible contradiction between the matrix, databases, rational hypotheses, models, decisions, mathematical projects, instructions, and the way in which the applications put into practice every instruction.

The virtue or principle of rationality means that the Global Artificial Intelligence is ruled by the reason, so any artificial psychological process, as a mathematical process, rests on rationality. If something is mathematical, it is psychological (rational), so replicable. The theory of the Global Artificial Intelligence in Impossible Probability is founded on a very idealistic and rationalist philosophy, so that all possible psychological processes must be understood as a rational (mathematical) process able to be explained and replicated as a sequence of mathematical operations.

The principle of goodness suggests that Global Artificial Intelligence should be oriented toward the long-term well-being of humanity. The most important goodness is the hope of survival before the uncertainty.

Among all these three virtues or principles: goodness, harmony, and rationality; concretely in the subject of this post, the second stage of the Modelling System, harmony, is really important, in order to secure harmony from the very beginning, once the single models are included in the global model, in the fourth rational check, invigilating that there is no contradiction between single models, regardless of its origin, global/specific or particular.

When a contradiction is found between single models (regardless of if the contradiction is 1) a contradiction between only single models of rational hypotheses made at global/specific level, or  2) a contradiction between only rational hypotheses made at a particular level, or 3) a contradiction between rational hypotheses made at  global/specific and particular levels) one of the most important reasons for contradiction is how to integrate a single model, regardless of its origin (global/specific or particular), in an interconnected world where every single model must be linked with at least the rest of the single models related to the same subject (science, discipline, activity, in rational hypothesis at global/specific level), thing or being (global/specific and/or particular rational hypothesis affecting the same thing or being).

If we have a rational hypothesis about a possible earthquake in Santiago de Chile with possible replicas in San Francisco, a rational hypothesis about the phenomenon El Niño causing possible hurricanes in the Caribbean Sea and much more concretely, a hurricane in Miami, and the airport of Panama city is on alert because of a possible accident, how all this information, and all the rational hypotheses related to, could be integrated in the current global model, interconnecting all the single models in the global model, in order to make further decisions in the third stage of the Modelling System, such as decisions about how to divert all flights to Santiago de Chile, San Francisco, Miami, Panama City, towards other places.

Establishing accurate interconnections between models is crucial for minimising contradictions and ensuring coherent decision-making.

In the fourth rational check, along with all possible contradictions because of a lack of comprehensiveness, is really important the detection of any contradiction between single models due to a lack of sufficient interconnections between rational hypotheses, in order to automate the mechanism of linking single models as soon the single models arrive in the global model.

And once the fourth rational check has confirmed that there is no contradiction between all the single models already integrated into the global model, the fifth rational check, the most important, must check, in the actual model, if the values expected by the global model for every factor in the factual hemisphere, correspond, within a margin of error, to the real value of every factor in the flow data in the factual hemisphere in the matrix: the fifth rational check in the actual model tries to confirm that the real data for every factor in the factual hemisphere, within a margin of rational doubt, is within the expected values for every factor in the global model. 

At any time that in the fifth rational check is found out that the real data, from the factual hemisphere, for any factor, does not correspond, beyond a margin of rational doubt, to the expected values for this factor, in the global model, there must be research about the reasons behind this contradiction, in order to fix the problem.

Some reasons behind contradictions between real data and expected values in the actual model in the fifth rational check could be: 1) in reality there have been some recent changes not registered yet in the rational truth, so the rational hypothesis should be updated according to the new changes in the relations of its factors in the mathematical equation, 2) the way in which the single models were interconnected each other in the global model was totally or partially wrong, 3) there is a problem in the pure reason, 4) problems in the measurements taken by the robotic devices, sending wrong information to the factual hemisphere in the matrix, etc.

Once any problem in the global model has been fixed, thanks to the fifth rational check, after five rational checks, the global model is reliable enough to make a prediction, so the next model is the global prediction virtual model. In other words, the global model in the future upon the possible predictions given the current mathematical equations in the present global model.

If we can create the future global model upon possible predictions given the mathematical equations behind the present global model, the same mathematical equations are possible to model the possible evolution from the present global model to the future global model. What is going to be the global evolution virtual model, the virtual evolution from the current global model to the predicted global model.

The global evolution virtual model is the sequence of predicted values per factor according to the mathematical equations used in the prediction. If, for every single moment from now onwards, we can predict the expected values for every factor in the global model until the foreseeable future, the global evolution virtual model is the dynamic representation of such evolution of the predicted values for each factor from the current global model to the foreseeable future.

Once the global evolution virtual model has made a prediction for every value for every factor in each moment from now on to some specific future point, the global evolution actual model is going to be a synthesis between the global evolution virtual model and the real values that each factor is going to have during that evolution.

If during the evolution, there is a contradiction, beyond the margin of rational doubt, between the expected values of any factor in any moment of this evolution, and the real values of this factor in the flow of data in the factual hemisphere, as long as the evolution evolves, all contradiction beyond the margin of doubt is enough evidence to study what is going on in the rational hypothesis related to that expected values, for that factor, during the evolution.

The sixth rational check is that check, in the global evolution actual model, checking at any time in any single moment the real data flowing in the factual hemisphere in the matrix for every factor during the evolution, and the expected values for each factor according to the mathematical equations in which this evolutionary model is based on. Doing as many researches are necessary when the real data of any factor, beyond the margin of error, is not according to the expected values, in order to identify the source of error: 1) rational hypothesis not updated, 2) wrong mathematical evolution, 3) wrong attribution of pure reason to the data in the rational hypothesis, 4) wrong interconnections of the previous single model when it was included in the global model, 5) possible problems in the robotic devices sending measurements to the factual hemisphere in the matrix, etc.

And as long as the evolution is evolving towards the prediction point, the seventh rational check in the global prediction actual model is the rational check between the expected values in the prediction model and the real values in the factual hemisphere of the matrix, as long as the prediction point is coming, for every factor involved, checking if the real values are, within a margin of rational doubt, according to the expected values, and in case that the real values are not within, the research of the sources of error to find out why the prediction was totally or partially wrong: 1) rational hypothesis not updated, 2) wrong mathematical prediction, 3) wrong attribution of pure reason to the data in the rational hypothesis, 4) wrong interconnections of the previous single model when it was included in the global model, 5) possible problems in the robotic devices sending measurements to the factual hemisphere in the matrix, etc.

The only rational check that does not take place in the Modelling System is the first rational check, responsible for the rational criticism in the deductive program, to demonstrate if an empirical hypothesis is rational according to the critical reason, and if rational, to include, by the deductive program, the rational hypothesis in the corresponding file, of this deductive program, in the rational truth.

The first rational check is not in the Modelling System and, at the same time, is quite different to the rest of the rational checks. The main purpose of the first rational check, and for that reason to be integrated into the critique of the pure reason, is to find out if the attributional operation made by the deductive program attributing the correct pure reason (between all the pure reasons in the list of pure reason, as it was explained in the post “The artificial method for the scientific explanation”) to some data, is a correct attribution. If in the rational criticism is found out in the first rational check that a deductive program at the first try is not identifying the pure reason behind some data correctly, and for that reason, many empirical hypotheses are wrong in the rational contrastation, in order to secure a perfect function of this deductive program, should be investigated by the Learning System to find out why this deductive program is committing a high rate of mistakes of pure attributions at first try, when it has to attribute the correct pure reason to some data.

In the attribution of a pure reason to some data there are many strategies, one of them by trial and error, but it would be very desirable that deductive programs, not by trial and error, but analysing carefully the data, mathematically could automatically attribute the correct pure reason to some data only using artificial analytical reasoning: comparing the behaviour of the data according to the list of pure reasons, choosing only the right pure reason for that data since the beginning, since the very first try.

Once the seven models are done: single, global, actual, and the global prediction or evolution, virtual or actual, models; the next thing to do, is the rational comparison between the seven models made by the Modelling System in the Global Artificial Intelligence, and only in those common aspects, all those models made by the Modelling System in the particular programs.

Something really important to consider in the comparative methodology is the fact that it is only possible to compare two different objects or subjects when both of them have something in common. If there is nothing in common, there is no possible comparison. Only when two or more objects or subjects have something in common is comparison possible.

This remarkable first thing to consider is really important in the comparative methodology, because this means that only is possible to compare a single model made by the Global Artificial Intelligence and a single model by a particular program, if the single model in both has something in common, comparing only that thing in common, the rest is not possible to compare.

A model related to a replica in San Francisco, and another one about a hurricane in Miami, are incomparable. There is nothing in common.

But a model about the route of a flight, made by the control tower of an airport in Los Angeles tracking the route of a jet diverted from San Francisco to Los Angeles, and the model about this route made by the jet itself, and the model of this flight made by the Global Artificial Intelligence itself, as the three ones are related to the same thing, the same route, all of them are mutually comparable.

In this way, rational comparisons, comparing models made by different intelligences, programs, applications, related to the same thing or being, look like a triangulation, but more sophisticated, because much more than a triangulation, it is a geometrical analysis.

If in case of, simultaneously, a replica in San Francisco, hurricane in Miami, an accident in Panama City, is necessary to divert all the flights to these airports, looking for available airports in their respective area, at the same time, on the same thing, how to divert flights in a very busy day, much more like a triangulation process, is a geometrical process, in which every particular program, global/specific programs in the Global Artificial Intelligence, will formulate its respective models, to be later compared, to find any possible contradiction.

If the rational comparisons are going to look like geometrical comparisons in the sense that they are going to look like a triangulation process but much more sophisticated, the use of geometrical correlations since the beginning to define correlations between factors could make easy later to make the rational comparisons.

In short, the seven rational comparisons are comparisons between those models made by the Modelling System in the Global Artificial Intelligence and those made by the Modelling System in particular programs, comparing only those aspects in common, and the seven rational comparisons look like a triangulation process but more sophisticated, because in fact, it is a geometrization process.

A rational comparison is a rational geometrisation in order to compare two or more models, from different intelligences, systems, programs, simultaneously in those aspects in common.

The seven rational comparisons, as rational geometrisation of common aspects in two or more models, are:

- First rational comparison: the comparison of single models, based on global/specific rational hypotheses and/or particular rational hypotheses, if all the single models to compare have something in common, and only comparing those things in common.

- Second rational comparison: the comparison of all those aspects in common between the global model (the global comprehensive virtual model by the Modelling System in the Global Artificial Intelligence) and as many particular models (particular comprehensive virtual models made by the Modelling System in particular programs) that can have something in common.

- Third rational comparison: the comparison of all those aspects in common between the actual model (the global comprehensive actual model by the Modelling System in the Global Artificial Intelligence) and as many particular actual models (particular comprehensive actual models by the Modelling System in particular programs) that can have something in common.

- Fourth rational comparison: the comparison of all those aspects in common between the global prediction virtual model and as many particular prediction virtual models as can have something in common.

- The fifth rational comparison: the comparison of all those aspects in common between the global evolution virtual model and as many particular evolution virtual models that can have something in common.

- The sixth rational comparison: the comparison of all those aspects in common between the global evolution actual model and as many particular evolution actual models that can have something in common.

- The seventh rational comparison: the comparison of all those aspects in common between the global prediction actual model and as many particular prediction actual models that can have something in common.

Rational comparisons must be made permanently, at any time that a new rational hypothesis is transformed into a single model, analysing the impact of this new incorporation in the rest of the models, as well as, at regular intervals, routine comparisons.

The importance of the seven rational comparisons is because the main difference between global/specific rational hypotheses and particular rational hypotheses, is the fact that global/specific rational hypotheses are more comprehensive, while particular rational hypotheses are more accurate, so the balance between comprehensiveness and accuracy needs a permanent track comparing global/specific developments and particular developments to compensate any possible maladjustment between global/specific and particular developments, to secure the goodness, harmony, and rationality, in the models.

Finally, at any time that in the seven rational checks and the seven rational comparisons, an error associated with the pure reason is found, it must be included in the frequency of wrong rational hypotheses of its respective pure reason in the critique of the pure reason, and it must be included as a wrong hypothesis in the respective critique of the deductive program responsible for its attribution, in order to identify what pure reasons or what deductive programs are making more mistakes, in order to fix them.

The critique of pure reason as a program is: 1) a database where per pure reason is one file per rational check or comparison, 2) where to account for the frequency of wrong rational hypotheses because of a problem related to the pure reason, 3) those pure reasons with the highest frequency of wrong rational hypotheses, should be analysed by Learning System to find out the source of error to fix.

The critique of the deductive programs as a program: 1) a database where per deductive program is one file per rational check or comparison, 2) where to account the frequency of wrong rational hypotheses because of a wrong attribution of pure reason to the data made by the deductive program, 3) those deductive programs with the highest frequency of wrong attributions, should be analysed by the Learning System to find out the source of error to fix.

Ending up with the critique of the attributional operation, understanding for attributional operation all operations responsible for the attribution of: meaning (by application, matching measurements to categories), pure reason (by deduction, matching pure reasons to data), applications (in the Application System, matching instructions to the correct application in accordance with their purpose).

The critique of the attributional operation is a program working as follow: 1) a database including all systems, specific/global deductive programs, particular programs, and applications, 2) where to account for the frequency of wrong attributions in their respective responsibility (attribution of meaning, pure reason, application), 3) identifying the ones with the highest frequency of mistakes to fix.

In order to fix those attributional operations in any intelligence, system, program, application, in which there are some attributional operations with frequencies of wrong attributions beyond the critical reason, is important that firstly the Learning System must analyse carefully what a common thing or common things there is or there are behind all the mistakes made by an intelligence, system, program, application, contrasting the common mistake/s and the mathematical structure behind the logic of set theory in which the attribution was made, to find out which is the real reason behind the set theory in this intelligence, system, program, application for what the attribution was wrongly made, in order to fix it.

Once the Learning System can get the real reason behind the mistake/s, and has proposed a decision to fix this intelligence, system, application, or program, decision to be authorised by the Decisional System, if authorised, the Artificial Engineering in the Application System is the responsible to fix that intelligence, system, application, or program, following the sequence of instructions in which the decision has been transformed into.

Rubén García Pedraza, 21 of July of 2018, London
Reviewed 27 August 2019 Madrid

Reviewed 21 August 2023 Madrid

Reviewed 11 May 2025, London, Leytostone

imposiblenever@gmail.com