Coordination spatiale émergente par champs de potentie

Nous abordons dans cet article la problematique du controle d'un systeme complexe a l'aide de techniques inspirees des sciences du vivant. A partir de l'exemple d'une simulation multi-agent, nous opposons une demarche descendante par decomposition fonctionnelle, que nous realisons avec des systemes de classeurs, a une demarche ascendante par emergence combinant auto-organisation et selection, que nous realisons a l'aide de champs de potentiel et d'algorithmes genetiques. Nous montrons en quoi la seconde demarche s'avere plus adaptee que la premiere pour mettre en oeuvre une coordination spatiale entre nos agents.

[1]  Olivier Sigaud,et al.  Being Reactive by Exchanging Roles: An Empirical Study , 2000, Balancing Reactivity and Social Deliberation in Multi-Agent Systems.

[2]  Ronald C. Arkin,et al.  The Learning Of Reactive Control Parameters Through Genetic Algorithms , 1992, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  C. Balkenius.  Natural intelligence in artificial creatures , 1995 .

[4]  Jacques Ferber,et al.  Les Systèmes multi-agents: vers une intelligence collective , 1995 .

[5]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[6]  Michael A. Arbib,et al.  Depth and detours: an essay on visually guided behavior , 1990 .

[7]  Tucker R. Balch,et al.  Motor Schema-Based Formation Control for Multiagent Robot Teams , 1995, ICMAS.

[8]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1985, Autonomous Robot Vehicles.

[9]  Olivier Sigaud,et al.  Vers une approche dynamique de la sélection de l'action , 2002 .

[10]  Olivier Simonin,et al.  Modeling Self Satisfaction and Altruism to handle Action Selection and Reactive Cooperation , 2002 .

[11]  Stewart W. Wilson.  ZCS: A Zeroth Level Classifier System , 1994, Evolutionary Computation.

[12]  R. Bellman.  Dynamic programming. , 1957, Science.

[13]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[14]  H. Van Dyke Parunak,et al.  Toward the Specification and Design of Industrial Synthetic Ecosystems , 1997, ATAL.

[15]  Jean-Claude Latombe,et al.  Numerical potential field techniques for robot path planning , 1991, Fifth International Conference on Advanced Robotics 'Robots in Unstructured Environments.

[16]  Olivier Sigaud,et al.  YACS: a new learning classifier system using anticipation , 2002, Soft Comput..

[17]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[18]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[19]  Michael A. Arbib,et al.  Perceptual Structures and Distributed Motor Control , 1981 .

[20]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[21]  Yoram Koren,et al.  Potential field methods and their inherent limitations for mobile robot navigation , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[22]  Ronald C. Arkin,et al.  Motor Schema — Based Mobile Robot Navigation , 1989, Int. J. Robotics Res..

[23]  F. Heider,et al.  Principles of topological psychology , 1936 .

[24]  Maja J. Mataric,et al.  Interaction and intelligent behavior , 1994 .

[25]  Stuart A. Kauffman,et al.  The origins of order , 1993 .

[26]  Tucker R. Balch,et al.  Social potentials for scalable multi-robot formations , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[27]  J. Leblanc.  THÈSE DE 3ÈME CYCLE , 1978 .

[28]  John S. Zelek,et al.  Complete real-time path planning during sensor-based discovery , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[29]  Stephen Cameron,et al.  Robot sheepdog project achieves automatic flock control , 1998 .