Specific Application System, third stage

The third stage of the specific Application System, is the third stage in the third step within the third stage in Specific Artificial Intelligences for Artificial Research by Deduction in the first phase, where the first Specific Artificial Intelligences for Artificial Research by Deduction or Application are built, to start as soon as possible the second phase of collaboration between them, getting ready the way for the first standardized Global Artificial Intelligence joining as many Specific Artificial Intelligences by Deduction as possible, third phase, at the same time that as many Specific Artificial Intelligences by Application as possible are joined in the Unified Application, fourth phase, transforming the remaining Specific Artificial Intelligences by Deduction in particular programs, and the remaining Specific Artificial Intelligences by Application in particular applications, for the creation of the first particular applications for particular programs, fifth phase, to experiment for first time the replication of a human brain at particular level, whose  results will be used later when the standardized Global Artificial Intelligences and the Unified Application are joined in only one intelligence, the integrated Global Artificial Intelligence, sixth phase.

Within the first phase, in Specific Artificial Intelligences by Deduction, the first stage is the specific matrix, the second stage the specific deductive program matching data and pure reasons (equations) to make rational hypothesis for further decisions in the third stage, which is going to be analysed in fourth different steps: first step Modelling System (modelling the rational hypothesis to make decisions), second step Decisional System (projecting the decisions authorising only those ones without contradiction and transforming the decision into  a range of instructions), third step Application System ( subdivided in outer instructions application sub-system to carry out all the instructions related to the real world, and the inner instructions application sub-system to carry out all the instructions related to applications or robotic devices working for the intelligence, creating new ones, or fixing or improving the existing ones), fourth step Learning System (analysing permanently the efficient level of the whole intelligence).

According to this structure, what I am analysing in these posts under the name of specific Application System is in reality the specific Application System as outer instructions application sub-system (in Specific Artificial Intelligences by Deduction in the first phase) to carry out the instructions provided previously by the specific Decisional System.

The organization of the specific Application System as outer instructions application sub-system is as follows: 1) first stage the database of instructions as a Russian Dolls System or positional encyclopedia, analysing in the first rational supervision that there is no contradiction among them, 2) second stage the process to carry out the instructions without contradiction, matching every instruction with the corresponding robotic device responsible for that task (carrying out the devices second, third, fourth, fifth, sixth rational supervisions), 3) third stage the seventh rational supervision sending reports the specific Application System to the Decisional System and the Learning System.

In turn, the second stage of the specific Application Sub-system as outer instructions application sub-system is organised as follow: 1) the second stage of the outer sub-system, matches every instruction with the corresponding robotic device sending the instruction to the corresponding robotic device, 2) first stage in the robotic device, the database of instructions sent by the outer sub-system to be applied by the robotic device, here the robotic device carries out the second rational supervision checking that there is no contradiction between the decisions sent by the second stage in the outer sub-system, 3) second stage in the robotic device, 3.1) the instructions without contradiction wait in the queue to be applied according to priority, time, order, carrying out the third rational supervision checking that no instruction is applied before the previous one is done, 3.2) when it is time to apply an instruction, before applying the fourth rational supervision checks that the ground conditions are favourable, 3.3) once the ground conditions are favourable, starts the implementation carrying out simultaneously the fifth rational supervision checking that is applied correctly in still favourable ground conditions, 4) third stage in the robotic device, once the instruction is completed, the robotic device sends a report with the results to the Decisional System, Learning System, and the Application System as outer sub-system.

Going on with the analysis of the specific Application System, as soon as the specific Application System, as an outer sub-system receives the reports from the robotic devices, the third stage for the specific Application sub-system is to make a new report in the seventh rational supervision to be sent to the Decisional System and Learning System.

In this process the third stage of the robotic device as sixth rational supervision and the third stage of the specific Application System as outer sub-system as seventh rational supervision, are pretty similar, with the difference that the application System as outer sub-system can have a more comprehensive point of view about all the process in the seventh rational supervision as third stage of the outer sub-system, while the sixth rational supervision within the third stage of the robotic device has a more limited perspective of the process.

Both processes, sixth rational supervision in the third stage of the robotic devices, and seventh rational supervision in the third stage of the outer application sub-system, are very similar, the only difference is the point of view, more limited in the sixth rational supervision made by robotic devices due to the point of view of the report is limited to the robotic device, while the seventh rational supervision made in the third stage of the outer sub-system is more comprehensive because can have a general overview about all the process.

The more limited point of view in the sixth rational supervision made in the third stage of the robotic device is due to the content of this report. The report made in the third stage of a robotic device to be sent to the Decisional System, Learning System, and Application System as outer instructions application sub-system, must be a final report where the robotic device must communicate to these other programs within the third stage of the Specific Artificial Intelligences, all what have happened along the process of application of an instruction.

The contents that the sixth rational supervision should include as final report of the third stage of a  robotic device after applying an instruction, are the followings: 1) the final report made by the robotic device in the third stage after the application of an instruction, must include any possible partial contradiction found in second, third, fourth, fifth, rational supervision, and how these partial contradictions were solved (because the final report is after completing the instruction is before hand understood that any possible contradiction found in its application was a partial contradiction possible to be solved by the robotic device itself not needing to send back the instruction to the source, in case of total contradiction the the instruction is back to the source, the Decisional System, unless there is no enough time for these changes, needing an extreme or high extreme instruction), 2) among the possible contradictions the most important ones those ones related to the fourth rational contradiction (mathematical operations vs robotic functions), and fifth rational contradiction (robotic functions vs robotic devices), and 3) finally, the final report made by the robotic device in the third stage after the application of an instruction, must include of course the result of the implementation of that instruction.

Further analysis of the fourth rational contradiction (mathematical operations vs robotic functions) will be carried out in the fourth rational critique in the Learning System, and further analysis of the fifth rational contradiction (robotic functions vs robotic devices) will be carried out in the fifth rational critique in the Learning System. But even being types of contradictions which are going to be analysed in the Learning System as fourth and fifth rational critiques, is not possible to skip the possibility that even the Learning System could be blind to some contradictions that skipping the rational critiques made by the Learning System, are contradictions that could be found in other controls, such as the rational supervisions in the Application System.

The fourth rational critique, in the same way of the rest of rational critiques, is a matrix counting the frequency of errors in the attribution of robotic functions to mathematical operations, so having analysed an increase of errors above a critical reason, in the attribution of a robotic function to a mathematical operation, the Learning System should analyse how this attribution works for this kind of robotic function, to improve the attributional system. The fifth rational critique is another critical matrix, but this time, it counts the frequency of errors attributing robotic functions to robotic devices.

Another different way to carry out the fourth and fifth rational critiques: only counting the frequency of errors related to robotic functions, and the number of errors related to robotic devices, analysing after the reports sent by different systems and devices, what percentage of errors are due to robotic problems, not favourable ground conditions, or any other rational explanation coming from external causes, and the remaining percentage of errors not due to these reasons, so having discard external (robotic problems, ground conditions, any other external cause) reasons for the remaining percentage of error, is possible to deduce that the remaining percentage of error not due to external error, is due to internal (psychological) error, this psychological (internal) error, excluding: robotic problems, negative ground, other external causes; could be possible due to a wrong attribution.

When the percentage of  psychological errors associated with a robotic function in the fourth rational critique, or the percentage of psychological errors associated with a robotic device in the fifth rational critique, is over a critical reason, is possible that this high internal error could be made by wrong attributions: a high error level associated with robotic functions because is wrong the attribution of mathematical operations to this robotic function in the fourth rational critique, or high error level associated with a device because the attribution of robotic functions to this robotic device is wrong.

In both cases the Learning System, after the analysis in the fourth and fifth rational critiques, having identified a high empirical probability of error in robotic functions and robotic devices, equal to or greater than a critical reason, so the reason could be explainable by wrong attributions, fourth rational contradiction (mathematical operations vs robotic function) and fifth rational contradiction (robotic function vs robotic device), then the Learning System must analyse the set of mathematical operations wrongly attributed to that wrong robotic function, to identify what there is in common in all these errors to identify which should be the right robotic function for these set of mathematical operations, or not existing yet the right robotic function along the intelligence, because the robotic device for these robotic functions has not been created yet, to order to the Artificial Engineering as inner instructions application sub-system the construction of that robotic device responsible for that robotic function.

In the same way in the fifth rational contradiction, robotic function and robotic devices, having realised the fifth rational critique a high percentage of errors not due to external causes, so this error could be due to internal reasons, wrong attribution, the Learning System must analyse what there is in common in all the robotic functions wrongly attributed to the same robotic device, to identify what there is in common among them to identify which robotic device should be the right one for these robotic functions, and in case that the right robotic device is not built yet, ordered to the Artificial Engineering the construction of the right one.

In any case, when the Artificial Engineering receives an order for the construction of an intelligence, program, application, or device, the Artificial Engineering firstly only makes a project to be sent to the Decisional System to be authorised not having contradictions with those technological projects regarding to the intelligence itself within the plan, once the Decisional System authorises the project, the Artificial Engineering makes the intelligence, program, application, device, as it was projected, and authorised, according to the request.

In any case, the fourth and fifth rational critiques, within the seven rational critiques, are done in the Learning System, I have only jot down some ideas that I will later develop by the time I develop the Learning System after the inner and outer Application System.

The reason to make this comments in this part of the analysis is to realise that, fourth rational contradictions (mathematical operations vs robotic functions) and fifth rational contradictions (robotic functions vs robotic devices) are going to be criticized in the Learning System, but even if these contradictions skip the control in the fourth or fifth rational critiques, these contradictions could be found in the seven rational supervisions.

In the report sent in the third stage of any robotic device after completing an instruction, the report is sent to the specific Application System as an outer sub-system, Decisional System, Learning System, the robotic device is going to inform about any contradiction or eventuality during the supervisions and implementation of any instruction. But limited to the point of view of the robotic device, only about this individual instruction, and sending a report including information from the second rational supervision in the first stage of the database of individual instructions in the robotic device, and the third, fourth, fifth, rational supervisions in the second stage of the device, whose information is synthesised in the sixth rational supervision informing about the whole process and results once the instruction is done by the device.

This report, sent in the sixth rational supervision in the third stage of the robotic device, is a mathematical analysis of all the evidence found: contradictions described in mathematical terms, ground conditions described in mathematical terms, problems found during the performance described in mathematical terms, and the result in mathematical terms.  Mathematical description of every contradiction, problem or circumstances, whose analysis must be done using the concrete Impact of the Defect for this robotic device and the concrete Effective Distribution for this robotic device, concrete Impact of the Defect and concrete Effective Distribution to this robotic device, because all robotic device is something concrete, every kind or type or device, must have been designed having as Impact of the Defect and Effective Distribution a concrete Impact of the Defect and Effective Distribution adapted to this type of device.

The way to measure the Impact of the Defect or Effective Distribution in the performance of an instruction given to an iron, or a car, or a watch, or a washing machine, or a lamp, is different, the categories to include in the list of errors in the Impact of the Defect when a car is not working well, or the list of categories of efficiency to include in a washing machine, are list of categories adapted to these concrete types of devices.

The categories to measure the efficiency of an aircraft, and the categories to measure the efficiency of a home automation system, are completely different; are a concrete list of categories adapted to these different types of technologies.

In the sixth rational supervision in the third stage of a robotic device, the final report consists of the classification of all the mathematical descriptions of: contradictions, problems, negative conditions, and the results; in a concrete list of errors in the concrete Impact of the Defect and a concrete list of categories related to efficiency in the Effective Distribution, to measure the impact or efficiency in the performance of an instruction, having categorized in a code system different levels of impact and efficiency, and having categorized some concrete contradictions (like fourth or fifth rational contradictions), problems (like problems due to lack of maintenance), or ground conditions (for instance a jet crossing a heavy blizzard having difficulties performing some instructions); in order to synthesis, in the final report that the sixth rational supervision in the third stage of any robotic device is going to make, a short encrypted message using a code system related to level of performance, according to the concrete Impact of the Defect and the concrete Effective Distribution, including in the list of errors or list of categories of efficiency: contradictions (fourth and fifth for instance), general problems, poor management under negative ground conditions, and results; along with some standard codes more specifically to fouth and fifth contradictions and very important problems, poor management, results.

As a result of the sixth rational supervision in the third stage of any robotic device, the Decisional System, the Learning System,  and the Application System, will have an encrypted report about level of impact or efficiency in the performance of that instruction by that device, and if necessary codes related to some important facts like important: contradictions, problems, ground conditions, results.

The result of the sixth rational supervision by the device is a concrete report from the concrete perspective of that concrete device, so limited to the concrete point of view of this device.

While the final seventh rational supervision made by the Application System as outer sub-system is a more comprehensive report having access to the whole range of concrete reports sent by every one of the concrete devices, in their corresponding concrete sixth rational supervisions, participating in the performance of a whole range of instructions belonging to the same decision.

The final report in the seventh rational supervision by the Application System as outer sub-system is a comprehensive report that could be done in two different  and compatible ways, as a singular final report about every singular instruction and as a comprehensive report, once the whole range of instructions belonging to the same decision is finished, containing a detailed mathematical analysis of the whole range of instructions belonging to the same decision.

For that reason, the seventh rational supervision could be sub-divided in two different supervisions, the first final  rational supervision as a singular seventh rational supervision,  and the second final rational supervision as a comprehensive seventh rational supervision.

The singular seventh rational supervision, or first final rational supervision, is the report made in the third stage of the Application System as outer sub-system about the achievement level of every singular instructions having as sources of information: the first rational supervision in the specific database of instructions, how was the attribution of the robotic function of this instruction to the robotic device, and the concrete report as a result of the sixth rational supervision made in the third stage of the robotic device, responsible for the implementation of that instruction.

In essence the singular seventh rational supervision, as a report about the implementation of an instruction filed by the Decisional System in the database of instructions as first stage in the Application System as outer sub-system, is the supervision of every singular instruction filed, whose report in a code system informs about: the result of the analysis of possible contradictions between this instruction and any other in the database of instructions, how the robotic function was attributed to a robotic device, the performance of the robotic device.

In short, the singular seventh rational supervision informs about: the first rational supervision, the attributional process of robotic functions and robotic devices, the sixth rational supervision-

The singular seventh rational supervision made in the third stage of the Application System as outer sub-system has as a result the report about all the contradictions, data, evidences during the performance of every singular instruction filed by the Decisional System in the Application System as outer sub-system.

While the second final rational supervision or comprehensive seventh rational supervision, is the supervision about how the performance of the whole set of instructions, belonging to the same decision, as it was analysed in the third stage of the Decisional System.

Because every instruction was filed by the Decisional System in the database of instructions according to sub-factoring level, sub-section, priority, time, and nth order within the range of instructions belonging to the same decision, the nth order is the reference number about what decision number belongs every instruction.

Having the nth order of every instruction within the range of instructions in which it is included, the range of instructions in which the decision was analysed by the Decisional System, this nth number is the number reference related to the range of instructions, in which the instruction was set up.

Having the whole set of instructions belonging to the same range of instructions, a nth number, a reference number of what set the instructions belong to and the nth order of every instruction to be applied by robotic devices, once the last nth instruction of a range of instructions is completed, then the comprehensive seventh rational supervision, having finalised the whole range of instructions with the last nth instruction, could make an assessment about the whole performance of that set of instructions belonging to the same range of instructions, belonging to the same decision.

While the singular seventh rational supervision in the third stage of the outer sub-system only informs about the singular performance of a singular instruction, regarding to: first rational supervision, attributional process, sixth rational supervision.

Now, the comprehensive seventh rational supervision in the third stage of the outer sub-system could make a more comprehensive analysis of this data, having as sources of information the whole range of singular seventh rational supervisions for every singular instruction belonging to the same range of instructions, of a decision made in the Decisional System.

Having the third stage of the outer sub-system as sources of information as many singular seventh rational supervisions for every instruction within a range of instructions, the comprehensive seventh rational supervision based on this set of singular seventh rational supervisions, is going to be like a summary about the comprehensive performance of the decision as a whole, once the whole set of instructions in which the decision was analysed, is finally performance by the robotic devices.

This comprehensive summary of all the singular seventh rational supervisions, is in essence, a resume about the average impact within the set of instruction, the average efficiency within the set of instructions, and all possible average of important errors, from the first to the sixth rational supervision including any incidence during the attributional process.

One of the aims of this comprehensive seventh rational supervision, as a summary of all the singular seventh rational supervision for every instruction within the same set, is to analyse if possible chains of errors due to a wrong attributional process, and if it is, which kind of wrong attributional process, wrong attribution of mathematical operations to robotic functions (fourth rational contradiction), or wrong attribution of robotic functions to robotic devices (fifth rational contradiction).

If once that a range of instructions is implemented is discovered that from the outset, and not due to external reasons, but probably due to psychological (internal) reasons, there is a low level of performance in every singular instruction by robotic devices, having absence of external reasons for this low performance level, so having reasons to deduce that this low performance level is due to internal reasons, once the report increase the errors in robotic functions and robotic devices, once is sent to the Learning System, in the fourth and fifth rational critiques, the Learning System must analyse how the decision was analysed by the Decisional System as to make so wrong decisions as to have so low performance level.

The design of the Learning System must include some levels of critical reasons for lots of processes, so once it has been realised an impact equal to or greater than, or an efficiency equal to or lower than, a positive or negative biased critical reason, automatically the Learning System must display a mathematical analysis of the causes behind that impact or efficient levels.

What this process requires is to set up models of Impact of the Defect and Effective Distribution that could share different systems, applications, devices, to analyse the impact or the efficiency in the same way, what later in the standardization process is going to help the standardization of all the specific Impacts of Defects and specific Effective Distributions in a Unified Impact of the Defect and a Unified Effective Distribution.

In the first phase there are only two different types of Impact of the Defect and two different types of Effective Distribution: 1) the concrete Impact of the Defect and the concrete Effective Distribution, both of them adapted to their respective concrete devices, and used for the sixth rational supervision in the third stage of the robotic devices, 2) the specific Impact of the Defect and the specific Effective Distribution, as those ones used in the third stage of the Application System as outer sub-system to make the singular seventh rational supervision and the comprehensive seventh rational supervision.

For every concrete type of robotic device, the concrete Impact of the Defect and the concrete Effective Distribution are adapted to their respective concrete type of device.

For every Specific Artificial Intelligence by Deduction, in the specific Application System as outer sub-system, the specific Impact of the Defect and the specific Effective Distribution, are adapted to the specific seventh rational supervision made in the third stage of this specific outer-subsystem.

The method for the design of specific Impact of the Defects, and specific Effective Distributions, in the third stage of the outer sub-system, to make the, singular and comprehensive, seventh rational supervisions, could be three different methods.

One method for the design of the specific Impact of the Defects and specific Effective Distributions adapted to the specific Application System as an outer sub-system, is to include in the specific Impact of the Defect all the categories related to defects in all the concrete Impact of the Defects working for that Specific Artificial Intelligence.

As a result, the specific Impact of the Defect is the addition of as many list of errors, as the first stage in the concrete Impact of the Defect, as working devices are working for the Specific Artificial Intelligences.

The Impact of the Defect defined as an application itself could be analysed in three stages: first stage of the Impact of the Defect the list of errors (ordered from the least important, nº = 1, the error number one is the least important error, to the most important, nº = N, the error whose cardinal number coincides with N is the most important error), second stage the computation of the Impact of the Defect, third stage the outcomes according to the results.

In this case, the seventh rational supervision, the outcome is the final report, the first final report as a singular report and the second final report as a comprehensive report, later sent to the Decisional System and Learning System for further decisions.

Having defined the Impact of the Defect as an application, so that the first stage of the concrete Impact of the Defect is a database of errors organised like a list from the least one to the most important one in that concrete device, the union of all these concrete lists of errors coming from every concrete Impact of the Defect, united in that specific Impact of the Defect working for the specific Application System as outer sub-system, will have as a result that the specific Impact of the Defect is the result to merge in one list of errors, all the different lists of errors coming from the different concrete Impacts of the Defects from all the devices working for this specific intelligence.

One way to organise the specific Impact of the Defect is as a result to add all the concrete lists of errors from all the concrete Impacts of the Defects in only one, that specific Impact of the Defect within the third stage in the outer sub-system.

Another second way to organise the Impact of the Defect could be: analysing how the concrete reports sent by the devices after the sixth rational supervision, are going to code and encrypt the information, information sent as codes related to levels of performance, impact, efficiency, and other codes related to important contradictions, negative ground conditions, or robotic problems,  how the different levels of performance, impact, efficiency, could be set up as different discrete categories of error or efficiency, and how the codes related to contradictions, ground conditions, robotic problems, could be set up as types of errors related to contradictions, ground conditions, robotic problems, in order that finally, having a whole set of discrete categories of levels of performance, impact, efficiency, and coded errors related to contradictions, negative ground conditions, robotic problems, to set up a definitive list of errors, ordered from the least important, nº = 1, to the most important, nº = N, according to how the level of performance or impact, or codes related to contradictions, ground, problems, could have different levels of impact in the final result, list which in the end will be the first stage in the specific Impact of the Defect in the third stage in the specific Application System as outer sub-system.

In the same way, analysing levels of performance and efficiency in the concrete reports sent in the third stage of the robotic devices after the sixth rational supervision, to set up discrete categories of performance and efficiency, as list of categories related to efficiency, to order from the first one, the least efficient, to the last one, the most efficient, all  the categories, list of categories which is going to be the first stage in the specific Effective Distribution working within the third stage of the specific Application System as outer sub-system.

Finally, the third way to organise the specific Impact of the Defect and the specific Effective Distribution, is as a synthesis of both methods already explained.

The specific Impact of the Defect could include: 1) all the concrete lists of errors coming from all the concrete Impact of the Defects from all the concrete robotic devices, 2) and the list of errors as distribution of discrete categories of levels of performance or impact, plus categories related to some codes of errors due to contradictions, negative conditions, robotic problems, where to categorize the concrete reports sent by the robotic devices as sixth rational supervision.

If at first sight the inclusion of some codes of low performance due to negative ground conditions could look like not fair, because is not due to a lack of efficiency in the robotic systems while performing an instructions, the truth is that if there is a robotic device with low level of performance when raining or snowing, if the Learning System identifies an empirical probability of low performance due to ground conditions, equal to or greater than a critical reason, one decision could be the adaptation of that device to these ground conditions in which it has low performance level.

The Learning System must analyse everything, and must be able to make decisions to improve the intelligence itself, sending the decisions to the Artificial Engineering, to make a project to be authorised by the Decisional System.

The most important advantage to organise the specific Impact of the Defect and the specific Effective Distribution including the list of concrete errors, and the list of discrete categories and some important codes related to contradictions, ground conditions, robotic problems, is the possibility that having a very complete list of possible errors throughout the whole Application System as outer sub-system, the possibility that the seventh rational supervision could go beyond the initial expectations.

In addition to the singular seventh rational supervision for every singular instruction, and the comprehensive seventh rational supervision assessing the performance of a whole set of instructions in which a decision was analysed, another third type of seventh rational supervision is the total seventh rational supervision in which the Application System as outer instructions application sub-system, having the concrete list of errors from every concrete device, could directly make a second control over the devices in addition to the sixth rational supervision, controlling directly the Application System how the devices are performing the instructions, analysing later on all the information received: by the sixth rational supervision, the singular seventh rational supervision, and the comprehensive seventh rational supervision; in a total assessment as a total seventh rational supervision, assessing all the information together in that specific Impact of the Defect built using the third method: uniting the concrete list of categories (first method for the specific Impact of the Defect), and the discrete categories plus some important codes (second method for the specific Impact of the Defect), union of both methods in only one, the third method for the construction of the specific Impact of the Defect, having as a result a very powerful tool to measure the total efficiency of the whole specific Application System as an outer instructions application sub-system.

Finally, I will end up with some comments about what kinds of auto-replications are done along the specific Application System as an outer sub-system. In general, as the third step in the third stage of the Specific Artificial Intelligence, the specific Application System is responsible for the performance in the real world of all the real objective auto-replications, as those auto-replications which having as their object the real world, their purpose is to protect and better the global model.

In addition to the performance, the implementation of real objective auto-replications, the specific Application System as an outer sub-system can make changes in the instructions, which could have further consequences in the plan, up to the point to cause knowledge objective auto-replications.

When any robotic device, in third, forth, or fifth rational supervisions realises that an instruction is not possible to be applied: because in the third rational supervision has realised that the previous instruction is not already done,  in the fourth rational supervision the ground conditions are not favourable, or there is any problem in the fifth rational supervision; as soon the robotic device stops the flow of instructions, the first thing that the robotic device must do is to calculate how much time there is for the impact, and the dimensions of the impact. According to the impact and time expected, if there is enough time to send back the instructions to the Decisional System to make new adjustments, or even, the Decisional System could send back the decision to the Modelling System, and even the Modelling System could send back the rational hypothesis to the second stage, if there is enough time for the recalculation of a decision following the normal procedure: rational hypothesis, model, project, decision, analysing the decision into a range of instructions, sending the new instructions to the Application System as outer sub-system to be applied, in that case the robotic device the only thing that it does is to stop the flow of instructions, sending back the Application System the instruction to the source, waiting for further instructions.

In this case, the new instructions sent by the Decisional System could be instructions from a decision categorised as normal, extreme, high extreme, and according to the priority, time, and order, the instructions will be processed by the Application System.

Otherwise, if the time expected by the robotic device for an important impact, is shorter than the time required to get a new decision if the instruction is back to the source, in that case the robotic device must make first an extreme or high extreme instruction, sending the report to the rest of systems, Decisional System, Learning System, Application System, and in this case the Decisional System having received a report of extreme or high extreme instructions by a robotic device, must include the instruction in the corresponding project, making as many adjustments as necessary in the plan to avoid further unexpected consequences. Adjustments categorised as normal, extreme or high extreme decisions, according to the priority level.

In this scenario, if the adjustments made by the Decisional System are adjustments over decisions made by Probability and Deduction, in that case the transformation in the Decisional System of an equation made by Probability and Deduction, is a transformation of an equation which is a model and a rational hypothesis as well.

The most important advantage of Probability and Deduction, is the fact that the deduction of a rational hypothesis by this method, allow the possibility that the same equation used to deduce the rational hypothesis, is at the same time the equation used as project in Decisional System, what means that a rational hypothesis is at the same time decision. If a decision product of Probability and Deduction is at the same time a rational hypothesis, any modification in any decision due to extreme or high extreme conditions found in third, fourth, fifth, rational supervisions, demanding adjustments in decisions, are adjustments of decisions which are likely to produce changes in the mathematical model as well as the rational hypothesis where originally this decision come from.

For that reason, the finding of extreme or high extreme conditions, in third, fourth, fifth rational supervision, demanding extreme or high extreme instructions, requiring later on adjustments in the decisions associated with, or having enough time not making extreme or high extreme instructions, sending back the instructions to the Decisional System, the Decisional System must make extreme or high extreme adjustments on decisions made using Probability and Deduction, at the end, what this changes caused by the third, fourth, fifth rational supervisions, are going to produce, if affecting decisions made using Probability and Deduction, is a chain reaction of changes in the plan, model and project, which will have further consequences in the rational truth requiring to modify the rational hypothesis associated with those decisions, according to the adjustments already made.

Any change in the rational truth (the database of rational hypothesis), ergo any change in the models, is an explicative knowledge objective auto-replication.

In addition, if the rational hypothesis changed was transformed into a factor as option within the specific matrix, the factor as option corresponding to that rational hypothesis must be changed according to the adjustments made in the corresponding decision, and if that rational hypothesis was transformed into a category in any Specific Artificial Intelligence by Application within the second phase of collaboration, that category must be changed according to the new adjustments on the decision associated with. And this last change would be considered as a comprehensive knowledge objective auto-replication.

As subjective auto-replications, as a consequence of changes caused in the Application System as an outer application sub-system, there are robotic and artificial psychological subjective auto-replications, to be managed by the Artificial Engineering after having the authorisation of its projects to make such changes by the Decisional System.

Robotic subjective auto-replications in the Application System as outer application sub-system, when as a result of lack of maintenance or robotic problems, a robotic device shows a low efficiency in the performance of instructions, which demands to be fixed by Artificial Engineering. As well as robotic subjective auto-replications must be considered when not having ready yet for some type of instructions a robotic device, so it is not possible to match this type of robotic function to any available robotic device, the Application System as outer instructions application sub-system sends to the Artificial Engineering as inner instructions application sub-system the order to construct the robotic device for this type of instructions, making first the Artificial Engineering the project, which having the authorization of the Decisional System, is built for that specific type of instruction.

And finally, as artificial psychological subjective auto-replication in the Application System as outer application sub-system, every time that sending reports to the Learning System, to be analysed for the fourth and fifth rational critiques, or when doing the rational supervisions, or in any other control throughout the Application System or the Specific Artificial Intelligence as a whole, is found rational contradictions regarding to the fourth rational contradiction: between mathematical operations and robotic functions; or fifth rational contradiction: robotic functions and robotic devices; which having being founded,  the Learning System ordered to the Designer of Artificial Intelligence, as part of the Artificial Engineering as inner instruction application sub-system, to fix the attributional process according to the results of the analysis of the common errors in these rational contradictions found out by the Learning System.

Ruben Garcia Pedraza, 17 November 2019, London

Reviewed 17 May 2025, London, Leytostone