New Autonomous Systems

Alain Cardon is a researcher at INSA Rouen, in France. He has previously held various university teaching positions within informatics and specializes in AI, multi-agent systems and machine consciousness.Mhamed Itmi is Associate Professor at INSA Rouen, in France. His research interests include decision support in AI, distributed systems and simulation using autonomous systems.

• Introduction ixList of Algorithms xiChapter 1 Systems and their Design 11.1 Modeling systems 11.1.1 Conventional systems 21.1.2 Complex systems 31.1.3 System of systems 31.2 Autonomous systems 51.3 Agents and multi-agent systems 61.3.1 The weak notion of agent 71.3.2 The strong notion of agent 71.3.3 Cognitive agents and reactive agents 81.3.4 Multi-agent systems 91.3.5 Reactive agent-based MAS 101.3.6 Cognitive agent-based MAS 111.4 Systems and organisms 131.5 The issue of modeling an autonomous system 13Chapter 2 The Global Architecture of an Autonomous System 172.1 Introduction 172.2 Reactivity of a system 172.3 The basic structure of an autonomous system: the substratum 182.3.1 A detailed example: smoothing the flow or urban traffic 202.4 The membrane of autonomous systems 222.4.1 Membrane and information 252.5 Two types of proactivity and the notion of artificial organ 262.5.1 Weak proactivity 262.5.2 Strong proactivity 272.5.3 Measuring proactivity with dynamic graphs 302.6 Autonomy and current representation 312.6.1 Current representation in an autonomous system 322.7 The unifying system that generates representations 33Chapter 3 Designing a Multi-agent Autonomous System 413.1 Introduction 413.2 The object layer on the substratum 413.3 The agent representation of the substratum: interface agents, organs and the notion of sensitivity 443.3.1 Artificial organs 463.3.2 Sensitivity of the corporeity 473.4 The interpretation system and the conception agents 473.4.1 The properties of a conception agent in the interpretation system 493.4.2 An example 523.4.3 Creating a conception agent 573.5 Aggregates of conception agents 583.6 The intent and the activity of conception agents 603.7 Agentifying conception agents 633.8 Activity of a conception agent 653.9 The three layers of conceptual agentification and the role of control 703.9.1 First guiding principle for the architecture of an autonomous system 743.10 Semantic lattices and the emergence of representations in the interpretation system 773.11 The general architecture of the interpretation system 843.12 Agentification of knowledge and organizational memory 863.13 Setting up the membrane network of an autonomous system 943.14 Behavioral learning of the autonomous system 96Chapter 4 Generation of Current Representation and Tendencies 1054.1 Introduction 1054.2 Generation of current representation and semantic lattices 1054.2.1 Openness and deployment: major properties of autonomous systems 1064.2.2 Incentive-based control and evaluation agents 1074.2.3 Evaluation agents’ access to organizational memory 1104.2.4 The role of evaluation agents in the extracted lattice 1104.2.5 The notion of dynamic lattices 1104.2.6 Algorithms for generating representations 1114.2.7 Mathematical interpretation 1154.3 The cause leading the system to choose a concrete intent 1164.3.1 Determination of intent 1184.3.2 Intent and tendencies 1204.4 Presentation of artificial tendencies 1234.5 Algorithm for the generation of a stream of representations under tendencies 134Chapter 5 The Notions of Point of View, Intent and Organizational Memory 1375.1 Introduction 1375.2 The notion of point of view in the generation of representations 1375.3 Three organizational principles of the interpretation system for leading the intent 1445.3.1 Principle of continuity engagement 1455.3.2 The bifurcation principle 1465.3.3 The principle of necessary reason and reliability 1475.4 Algorithms for intent decisions 1475.6 Organizational memory and the representation of artificial life experiences 1515.7 Effective autonomy and the role of the modulation component 1565.8 Degree of organizational freedom 159Chapter 6 Towards the Minimal Self of an Autonomous System 1616.1 Introduction 1616.2 The need for tendencies when leading the system 1616.3 Needs and desires of the autonomous system 1646.4 A scaled-down autonomous system: the artificial proto-self 1686.5 The internal choice of expressed tendencies and the minimal self 1716.6 The incentive to produce representations 1766.7 Minimal self affectivity: emotions and sensations 1796.8 Algorithms for tendency activation 1826.9 The feeling of generating representations 188Chapter 7 Global Autonomy of Distributed Autonomous Systems 1977.1 Introduction 1977.2 Enhancement of an autonomous system by itself 1977.3 Communication among autonomous systems in view of their union 2017.4 The autonomous meta-system composed of autonomous systems 2047.5 The system generating autonomous systems: the meta-level of artificial living 207Conclusion 211Bibliography 213Index 215