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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
There are many different ways of generating representations. This includes representations generated by living beings while comprehending reality in order to act; representations generated by the Universe during its extensive unfolding, creating physical elements and living beings; and the direct representation of elements through an animal's sixth sense. To this list we must now add the creation of artificial consciousness, which generates representations that resemble the mental representations of humans. These representations allow robotic systems to communicate directly with each other. Fundamental Generation Systems develops a theory which presents, from the beginning, the function of this sixth sense called the "sense of informational comprehension". This sense is understood as an ability to use the informational foundations of the Universe via a dedicated cerebral domain found in every animal.
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Veröffentlichungsjahr: 2023
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Table of Contents
Cover
Title Page
Copyright Page
Preface
Introduction
1 Systems and their Designs
1.1. System modeling
1.2. Autonomous systems
1.3. Multi-agent systems
1.4. Organizations and systems
1.5. The problem of modeling an autonomous system
1.6. Agents and multi-agent systems
2 Reliability of Autonomous Systems
2.1. Introduction
2.2. Dependability of a system
2.3. Reliability diagram
2.4. Reliability networks
3 Artificial Intelligence, Communication Systems and Artificial Consciousness
3.1. Introduction
3.2. Evolution of computer science
3.3. Evolution of artificial intelligence
3.4. Radical evolution of computing and AI towards fully communicating systems
3.5. The computer representation of an artificial consciousness
4 The Informational Substrate of the Universe and the Organizational Law
4.1. Introduction
4.2. The fundamental principles of the informational model of generation of the Universe
4.3. The notion of generating information in the Universe
5 The Informational Interpretation of Living Things
5.1. Introduction
5.2. Origin of living things with bifurcation of the organizational law
5.3. The informational action of reproduction of living things
5.4. The human species in the organizational evolution of living things
6 The Interpretation of Neuronal Aggregates
6.1. Introduction
6.2. The systemic layer and the regulators including the informational regulator
7 The Sense of Informational Comprehension of Living Organisms: The Sixth Sense
7.1. Introduction
7.2. The five usual senses and the use of the informational substrate
7.3. The sense of informational comprehension or the sixth sense
7.4. Common use of the sixth sense
Conclusion
Appendices
Appendix 1: Binomial DistributionBinomial Distribution
Appendix 2: Geometric DistributionGeometric Distribution
Appendix 3:Poisson DistributionPoisson Distribution
Appendix 4: Exponential DistributionExponential Distribution
Appendix 5: Normal DistributionNormal Distribution
Appendix 6: Lognormal DistributionLognormal Distribution
Appendix 7: Weibull DistributionWeibull Distribution
Appendix 8: Pareto DistributionPareto Distribution
Appendix 9: Distribution of Extreme ValuesDistribution of Extreme Values
Appendix 10: Asymptotic DistributionsAsymptotic Distributions
References
Index
Other titles from in Science, Society and New Technologies
End User License Agreement
List of Illustrations
Chapter 1
Figure 1.1.
A peer-to-peer organization around a network
Chapter 2
Figure 2.1.
Different components of SoR
Figure 2.2.
Reliability–failure relationship
Figure 2.3.
Different indicators
Figure 2.4.
Series system
Figure 2.5.
Parallel system
Figure 2.6.
Parallel–series system
Figure 2.7.
Series–parallel system
Figure 2.8.
Complex system
Figure 2.9.
Series diagram
Figure 2.10.
Parallel diagram
Chapter 3
Figure 3.1.
Organizational diagram of an artificial psychic system. For a co
...
Chapter 6
Figure 6.1.
The organizational architecture of the psychic system with its f
...
Figure 6.2.
The comprehension of the emerging representation in the consciou
...
Appendix 5
Figure A5.1.
Influence of the standard deviation at a constant mean. Probabi
...
Figure A5.2.
Influence of the standard deviation at a constant mean. Distrib
...
Appendix 6
Figure A6.1.
Influence of the standard deviation at a constant mean. Probabi
...
Figure A6.2.
Influence of the standard deviation at a constant mean. Distrib
...
Figure A6.3.
Position of median, mode and mean, to be compared with μ. Proba
...
Appendix 7
Figure A7.1.
Weibull distribution
Guide
Cover Page
Title Page
Copyright Page
Preface
Introduction
Table of Contents
Begin Reading
Conclusion
Appendix 1 Binomial Distribution
Appendix 2 Binomial Distribution
Appendix 3 Poisson Distribution
Appendix 4 Exponential Distribution
Appendix 5 Normal Distribution
Appendix 6 Lognormal Distribution
Appendix 7 Weibull Distribution
Appendix 8 Pareto Distribution
Appendix 9 Distribution of Extreme Values
Appendix 10 Asymptotic Distributions
References
Index
Other titles from in Science, Society and New Technologies
WILEY END USER LICENSE AGREEMENT
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Digital Sciences Set
coordinated byAbdelkhalak El Hami
Volume 4
Fundamental Generation Systems
Computer Science and Artificial Consciousness, the Informational Field of Generation of the Universe, the Sixth Sense of Living Beings
Alain CardonAbdelkhalak El Hami
First published 2023 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.
Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:
ISTE Ltd27-37 St George’s RoadLondon SW19 4EUUK
John Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USA
www.iste.co.uk
www.wiley.com
© ISTE Ltd 2023The rights of Alain Cardon and Abdelkhalak El Hami to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s), contributor(s) or editor(s) and do not necessarily reflect the views of ISTE Group.
Library of Congress Control Number: 2023930941
British Library Cataloguing-in-Publication DataA CIP record for this book is available from the British LibraryISBN 978-1-78630-873-3
Preface
There are many different ways of generating representations. This includes representations generated by living beings while comprehending reality in order to act; representations generated by the Universe during its extensive unfolding, creating physical elements and living beings; and, the direct representation of elements through an animal’s sixth sense. To this list we must now add the creation of artificial consciousness, which generates representations that resemble the mental representations of humans. These representations allow robotic systems to communicate directly with each other.
In our research, we have stated that the Universe, with all its material elements, in addition to the living organisms on Earth, was generated and then organized on a strictly informational substrate. This informational substrate – which is a set of virtual processes and relations – founds space, time and the elements of the Universe. The Universe is founded on a set of informational fields that constitute its foundation and deployment. It is not a set of elements that randomly structure themselves on available nothingness forming space, but a system that is conceived and generated, strictly autonomous and in self-organized development.
Today, computer science, along with artificial intelligence, is moving towards total communication between all humans and between all computerized systems, which is a transposition of the sixth sense in the field of sophisticated techniques. In addition, there is the generation of artificial consciousness systems that allow robotic systems to communicate directly with one another, generating shared or even common artificial mental representations, which goes beyond the sixth sense in animals.
In Chapter 1, we present systems and their designs. We explore the modeling of systems, traditional systems, complex systems, systems of systems, autonomous systems, multi-agent systems and finally organisms and systems.
Chapter 2 presents the reliability of autonomous systems. It highlights the reliability of a system, its general concepts, the failure and repair rates, the average estimators and some methodological tools for modeling the reliability of systems (serial, parallel, mixed) and finally the complex systems.
Chapter 3 presents computer science, artificial intelligence, communication systems and artificial consciousness. Today, computer science is a core discipline in science and society due to the innumerable uses of software that constantly communicate. We will trace its history, show how significant artificial intelligence has become and witness the move towards a distributed, highly communicating and autonomous artificial consciousness. These continuous communications between humans through computerized systems come from a tendency to communicate, which human technology has strongly developed and whose source comes from the informational substratum of the Universe, which is essentially communicational.
Chapter 4 presents the informational substrate of the Universe and the organizational law. We present the Universe as an organizational system generating space and physical elements. The Universe was created by a very specific soliciting element, which produced informational elements that created space and structured elements in a continuous way with spatial and temporal stability. We have therefore shown that the Universe is an organized emergence with informational components, whose role is to aggregate into physical elements on an informational substratum that carries out a self-control incentive. This generation is achieved by following an organizational law that operates at the level of the informational substratum. The model we have presented allows us to consider the Universe as the continuous generation of a self-organizing system that creates its space, the matter of its physical elements, based on specific and absolutely continuous informational communications.
Chapter 5 presents the informational interpretation of the living. In particular, the origin of life with a ramification of the organizational law, the informational action of reproduction of life with morphological patterns and the human species in the organizational evolution of life. We can consider that all living organisms on Earth are stabilized structures of informational fields that are part of a general multi-scale organization, localized in the geographical areas that make up the terrestrial ecosystem, in order to behave and develop there by generating multiple species. It is thus put forward that all living things on Earth are immersed in an informational domain that comes from the informational substratum of the Universe, which is based on a considerable set of informational fields that make it possible to structure the organisms by incentives to their organizations, with control over their generation. All living organisms are therefore the very finely organized material realizations of the reifications of these informational fields.
Chapter 6 is devoted to the representation of human consciousness with its senses. It presents the interpretation of neuronal aggregates, the systemic layer and the regulators, including the informational regulator. The neuronal system operates in terms of parallel production of multiple neuronal signals which, by their associations and aggregations, form a very complex whole that can be interpreted as a structure of dynamic forms that combine with one another. This is a structure made up of activities and informational exchanges that carry sensitive and cognitive indications at a certain level.
Chapter 7 is devoted to the informational understanding of living organisms: the sixth sense. This sixth sense is unlike the five usual senses, because it is a global and organizational comprehension of elements that are outside the understanding of the five usual senses. We will show how this sense is a comprehension of elements of the informational network that forms the organization of all elements on Earth, by developing what this informational comprehension of communicating informational envelopes is, which is completely different from a visual comprehension of a world of objects with measurable positions in space. In addition, we will explain the notion of magnetism used by healers.
February 2023
Introduction
We therefore assume that the informational substratum of the Universe is generated from a generative component that produces innumerable informational components, each one also producing others, according to a general organizational law that enables the generation and expansion of our whole Universe. Each created component either becomes an element with neutrality of activity, and is therefore an element of space, or is an element with permanence of activity and is a basic quantum element. The active elements can generate others according to the organizational law and the context. These transformations are therefore subject to an organizational law that allows the organized generation of the Universe with all its elements. The Universe has been created from a generating component with informational energy and, by continuous generation, has produced informational components that reproduce themselves according to the underlying organizational law, and constitute space and quantum particles. According to the general tendency defined by the organizational law that drives the substratum, these particles will aggregate to form molecules and then physical material elements, in a specific time-frame, which will be the speed of the unfolding of the Universe in generation. The physical Universe is thus an extensive unfolding, which is self-organized by an informational system.
All the generated informational components are elements whose role is to form aggregations, following the organizational law that drives the formation of the Universe. The structured physical elements created will each have an informational envelope, a specific informational field, which will indicate their specificities and current states, and which will connect them to the other elements by informational links that are fields, in order to continue the aggregations and proceed towards the formation of massive elements. The notion of materiality is thus based on the informational substratum of the Universe that makes all the elements exist, producing structured aggregates that have structural stability.
The organizational law is the cause of the evolutionary living on Earth, which benefited from favorable conditions: stability and the existence of water. All living organisms have an informational envelope enabling their generation, organization and organically coherent functioning. This envelope is the reason for the formation of new species in an informational management of reproduction. This physical informational envelope is the synthesis of the informational envelopes of each organ, which allows coherence in the functioning network of any living organism. The general envelope of the organism describes the general state of the organism, whether it is in good or bad condition. Living beings, including all animals, use this envelope to directly and immediately understand the situation of certain other living beings that they know and are interested in: they make use of their sixth sense.
Human thought is complex. Placing ourselves within the framework of constructing an ideal multi-character representation that is generated and felt, in addition to the use of language, and under multiple simultaneous constraints, to think is to construct a series of mental representations on themes. Constructions and reconstructions produce the sensation of thinking by their existence and characters. We can define what this system is capable of producing as a set of forms that can be manipulated, while considering the depth and richness of the experience that allows us to define them, with tendencies expressing the ability to abstract, formulate, open up to the knowable external world and the five senses, which are always usable.
Today, it is generally agreed that animals are endowed with a sixth sense, which is an ability leading to the production of sensitive and conceptual representations, expressing the situations and movements of particular individuals or the approach and state of known physical places, but which are not apprehensible by the five usual senses. We will develop a theory presenting the function of this sixth sense, as well as its origin, something which has not yet been done, and we will call this sixth sense the “sense of informational comprehension”. This sense will be conceived as an ability to use the informational substratum of the Universe, with a specific cerebral domain which exists in all animals. There is therefore a very particular cerebral domain in the brain, which makes it possible to communicate through the informational links of the substrate. This sixth sense is of considerable importance in the living world, as it causes a tendency in all these organisms towards living in groups and forming associations by systematically using the informational envelopes of the participants in the groups. Using this sense, animals are able to directly understand the general state of other organisms and their spatial location, by accessing their informational envelopes. In humans, it is their tendency to form organized groups. It is therefore a very important ability for a human being at the social level to voluntarily and socially develop their use of this sixth sense, as it enables each human to carry out direct informational communication with a great many other humans, by understanding their organizational states, their proximities or their distances, and thus using this informational immersion to move towards ethical sharing, peace and the organizational unification of all living beings.
Present-day computer science, along with artificial intelligence, is moving towards total communication between all humans and between all computerized systems, which is a transposition of the sixth sense in the field of sophisticated techniques. In addition, there is the generation of artificial consciousness systems that allow robotic systems to communicate directly with one another, generating shared or even common artificial mental representations, which go beyond the sixth sense in animals.
1Systems and their Designs
1.1. System modeling
A system is normally designed to provide services. It consists of hardware, software and human resources to meet a specific, clearly defined need. The history of science is full of such systems. Their manufacturing methods have evolved over time as a result of the experiences acquired, the evolution of technologies and the modeling approaches. Various notions can intervene in the description of a system. They concern its components and their groupings, their interactions and the interactions with the environment of the system.
Generally, the notion of a system implies interdependent entities, whose functionalities are fully specified. The system is clearly defined according to an equational and functional approach, in a top-down or bottom-up iterative process. It is top-down when the approach is analytical and allows each part to be broken down into sub-parts, which are sub-systems in their own right. The reverse iterative process – bottom-up – is instead oriented towards the construction of sub-systems from the more basic ones. The implementation of the system and its possible evolution are predetermined in a narrow and precise field, the functionalities being able to relate to various and varied fields: electrical, electronic, data-processing, mechanical, etc.
With the evolution of systems and the progress made in information and communication technologies, we can observe a trend of building large systems with an increasing number of strongly interconnected elements and handling very large amounts of data.
There are different types of systems, but we will only consider two separate classes here: traditional systems and complex systems.
1.1.1. Traditional systems
The so-called individual or traditional systems are those whose inputs/outputs are completely specified, in the sense that everything has been designated for them at their origins. They form the vast majority of the systems we encounter. This is the case of a management application, scientific calculation or musical creation, for example. The elements constituting these systems are determined to carry out a specific process for which the system was formatted. This processing produces actions or results to be exploited, which is the purpose of the system. Even though a system is operational but still evolving, as long as it has a project manager, it is a traditional system. Everything is framed for such systems. An example would be an ATM. All the conditions of use must be clearly defined and supervised to allow it to function normally, in order to meet the demands of the customers and the bank. Operation in a degraded mode or in the case of unforeseen events must also be considered.
The development of computer networks contributes to the evolution of these traditional systems, by increasing the possibilities of exploiting their resources and by enriching their possibilities of interaction. This also contributes to the complexity of these systems, but without changing their basic nature: they remain traditional. Service-oriented architecture (SOA) is one example. The development of cloud computing from the perspective of the services offered is an illustration. The accumulation of systems for the accumulation of services offers systems that also remain traditional as long as the services obtained can be deduced from the sum of the services of the systems that make them up. The integration of systems to produce new desired services produces a new traditional system, by its functional description. Malfunction situations are normally also managed.
1.1.2. Complex systems
The literature describes many types of systems, with a particular interest in complex systems, mainly because of the non-predictability of their behavior. They generally concern fields where multidisciplinarity is expressed (economy, neuroscience, insect societies, etc.).
Authors generally agree to the idea of defining a complex system as a system that is composed of a large number of interacting entities, whose behavior cannot be deduced from the behavior of its parts. Hence, the concept of emergence: the complex system has an emergent behavior that cannot be deduced from any of the systems that constitute it. It is not the large size of a system that makes it complex: if its parts have been designed, structured and interact in a known way, then it is not complex. However, a non-complex system becomes complex as soon as a human is part of it.
Complex systems have many behavioral characteristics that are sought after for study: self-organization, emergence, non-determinism, etc. The common approach to the study of complex systems is simulation, because it allows us to get an idea, even though only partially, of the system’s behavior. Complex systems show an autonomy of behavior that we will specify later, by linking it to the notion of proactivity.
Any information system that includes both functional elements and elements that consider human actions and decisions, as well as manage multiple points of view, is a complex system where the components are placed at multiple scales that can vary from one to another.
1.1.3. Systems of systems
The notion of system of systems (SoS) (Jamshidi 2008) has been introduced without being outlined by a clear definition. Several approaches are suggested in the literature. At first glance, the notion implies the existence of several systems that operate together (Zeigler and Sarjoughian 2013). From this notion of SoS, we exclude all that brings us back to the case of traditional systems, which can thus be reduced to centralized management, as is the case for a family of systems. Among the SoS approaches, let us mention the case of the super system comprising complex independent elements that interact for a common goal, or that of a large-scale system of competing and distributed systems.
The most common notion of SoS (sometimes called complex SoS) (Maier 1999) implies a set of systems, each one having been defined for its own services and for which it is managed, but without justifying its presence in the global system. The global system must also exhibit emergent behavior. An SoS thus benefits from the activity of these systems, in order to build its own. There can be a large number of these systems, but that can also change. Each system can join or leave the global system at any time. This sheds light on the absence of a predefined objective for the global system, as well as the difference in the mode of control. In other words, the overall goal of an SoS may not have been defined a priori.
The scalability characteristic of SoS through integration of other systems can be due to reasons such as rapid technological change or budgetary reasons. These give an SoS the ability to be “quickly” augmented or reduced by parts (Cardon and Itmi 2016). This point of view shows that the engineering of SoS cannot be conventionally carried out, as for traditional systems, according to a top-down or bottom-up process.
This approach highlights a particular architecture, with a functioning that implies coordination/regulation and a basis that is manifested by an orientation towards one or several goals. This raises various questions concerning the notion of autonomy, the reason for organization in autonomous systems, the notion of coherence of behavior and the orientation of the activity, as well as the control of such a system.
Distributed simulation is a way to approach SoS. It is similar to the simulation of a peer-to-peer system, but necessary elements are required for an understanding of the emergent behavior (see Figure 1.1).
Figure 1.1.A peer-to-peer organization around a network
1.2. Autonomous systems
The notion of an autonomous system (in the field of robotics) implies a system that has the capacity to act by itself, to carry out actions that are necessary for the realization of predefined objectives responding to stimuli which, in robotics, come from sensors. Various approaches to the notion of autonomy exist in the literature, because the ability to act by oneself can take on different characteristics, from the activity of an automaton to that of a living being, as well as through those of a system that has the ability to act by learning.
Along with the notion of an autonomous system, which represents an advance on systems that are not advanced, there is the notion of intelligent control, which represents an advance on the notion of control. Intelligent control involves algorithms, linguistics and mathematics applied to systems and processes (Cardon and Itmi 2016), and for hierarchical systems, control is described in a three-level model, which is widely referenced in the literature. We will mention it briefly in what follows and refer the reader to the original article for more details. In short, the three levels are:
the organizational level;
the coordination level;
the execution level.
It should be noted that in the first level, the imitation of human functions is sought with an interest in analytical approaches. We can make the following observations about this approach:
The proposed model is a hierarchical (top-down) model, defining a machine that is subject to the dictates of the organizational level (see how the information feedback is done).
It is an approach that heavily relies on calculation and ignores the work on knowledge. As a result, processing is done in a “closed world” and does not seem to us to adapt to multidisciplinarity.
The definitions associated with the various levels construct this difference: for example, the first two levels do not consider the notions of organization and emergence.
The integration of two systems does not seem possible to us with the approach of Sarano (2017). What about the integration of a proactive system? The notion of proactivity is completely absent. Working on a priori knowledge is to already have some control, a proactive element cannot be well controlled.
Another important point is the absence of the notion of point of view, although it is a major one in our case. We start from the hypothesis that knowledge depends on the point of view, which relativizes it. Knowledge is therefore subjective, and we do not assume absolute truth.
In this work, we propose a model of autonomous systems that has been directly inspired by the living world and which differs from the model above. Our approach will show that we do not address the same problems as strictly analytical approaches.
In order for the system to behave like an autonomous organism, it must have an architecture that is composed of elements considered as artificial organs and, above all, at the elementary level, it must be designed by computer elements that also have minimal autonomy, which are sensitive to their environment and which are modified by the simple fact of being activated, of functioning.
1.3. Multi-agent systems
A multi-agent system (MAS) is a system composed of a set of agents forming an organization, in other words, an identified system that reorganizes itself through its actions and the relations between its elements, that conforms and re-conforms itself to carry out its action on the environment. Unlike the systems developed in artificial intelligence, which simulate certain capacities of human reasoning in a certain field, based on knowledge structures where an inference-type reasoning mechanism operates, MAS are conceived and implemented as a set of agents which interact according to modes of cooperation, competition and negotiation, and which therefore continuously conform their behavioral organization to identify the most effective form each time.
A MAS is characterized by the following:
Each agent has limited information and problem-solving capabilities. It has knowledge and appreciation that are only partial or local to the general problem that the MAS must address and solve.
There is no global and centralized control of the MAS, which is the main point.
The data of the system are decentralized and taken by some system interface agents, by managing the distribution and temporality problems.
The calculation of the solution of the problem that the system must solve at each phase of interpellation, and thus the functioning of the MAS, is done by managing the coordination of all the agents, and this is achieved in an asynchronous way in order to identify a small set of agents, by emergence, that will perform the action and act on the problem.
Moreover, a MAS can be seen as a set of agents, located in an environment that is composed of other agents and objects different from the agents. Indeed, the agents use objects of the environment (object in the strictly functional and computing sense of the term), which are simply reactive elements providing information and producing functional actions. The agents have a capacity to interpret the information given by the methods of these objects, as well as the behavior of the other agents, taking the time to do so. These agents thus use the objects and communicate with other agents in order to achieve their objectives. In the system that we define, this makes it possible to distinguish all of the information to be comprehended, which will be produced systematically by the objects whose role it is to do so, from their analyses and conceptual interpretations at multiple levels, which will be the purpose of the organization of the agents.
1.4. Organizations and systems
In all that follows, we will focus on open systems, in other words, those that interact with their environment. Such systems are understood as a set of elements in relations, organizing the action of their interdependent elements and producing actions on their environments. Such systems are therefore both the set of their elements and the continuous relations allowing them to exist and act on their environments.
In biology, an organism is the set of organs of a living being. An organ is a term in biology that designates a set of tissues, whose activity performs a specific physiological function or small set of functions. This organ is an element of a biological system that performs all the functions of a specific domain. Organs and their relations are represented by anatomical diagrams, anatomical charts, etc., and all these particular biological systems are placed in the unified whole that constitutes and forms the living organism. We can then identify the organism with the living being.
A comparison can be made between certain artificial systems and natural organisms, by examining their compositions and the underlying relations.
The relations between the elements of a system can be considered as information manipulation. For this, we will consider two levels in a system:
the level of physical elements, formed by basic elements and aggregates of such elements;
the level of exchange and manipulation of information between physical elements.
We therefore adopt an approach that transposes the fundamental nature of living organisms into the domain of artificial systems. This will involve an original design approach and the use of very specific elements.
1.5. The problem of modeling an autonomous system
Artificial corporeality is a set of distributed electronic and computer elements with precise functions that are managed locally by computer processors, but with an overall unification of all these actions, making it possible to give meaning to their links and actions by coordinating them in a continuous way.
An artificial organ will be a specific element, formed by the union of a particular electronic system activating electromechanical elements and a computer control system unifying these elements, making it possible to represent their precise functionalities in order to use them in very coordinated ways. This organ is arranged in a corporality made of multiple other organs, and it will be managed as a highly coactive element with all other elements considered as organs.
To design an artificial organism, it will be necessary to rely on two major concepts that will lead to the definition of its complex architecture:
One of these concepts will involve the organization of the physical components of the system, which will be considered as its organs and which will form its highly organized corporality.
The other major concept will be to design an interpretation system that continuously manages the system’s behavioral states, interpreting and processing all the information it comprehends, using all its knowledge. This interpretation system will make it possible to continuously generate sequences of its own representations, with intention, while deriving what it comprehends, what it conceives, what it represents to itself and what it wants, thus committing it to desired and continuously interpreted actions.
It is quite clear that it is a question of providing the system with a representation sequence generator, so that it can express its intentions, its desires and its wishes, by experiencing sensations. The design of such a system that fully uses its corporality and comprehends itself as an organism is the key to the current notion of autonomy.
