Bio-inspired Mechanisms for Artificial Self-organised Systems

Research on self-organization tries to describe and explain forms, complex patterns and behaviours that arise from a collection of entities without an external organizer. As researchers in artificial systems, our aim is not to mimic self-organizing phenomena arising in Nature, but to understand and to control underlying mechanisms allowing desired emergence of forms, complex patterns and behaviours. In this paper we analyze three forms of self-organization: stigmergy, reinforcement mechanisms and cooperation. For each forms of self-organisation, we present a case study to show how we transposed it to some artificial systems and then analyse the strengths and weaknesses of such an approach.

[1]  R. Jeanne,et al.  Forager success increases with experience inPolybia occidentalis (Hymenoptera: Vespidae) , 1992, Insectes Sociaux.

[2]  Marco Dorigo,et al.  Ant algorithms and stigmergy , 2000, Future Gener. Comput. Syst..

[3]  Jean-Louis Deneubourg,et al.  Information Processing in Social Insects , 1999, Birkhäuser Basel.

[4]  Marco Dorigo,et al.  Swarm intelligence: from natural to artificial systems , 1999 .

[5]  Guy Theraulaz,et al.  The mechanisms and rules of coordinated building in social insects , 1999 .

[6]  P.-P. Grasse La reconstruction du nid et les coordinations interindividuelles chezBellicositermes natalensis etCubitermes sp. la théorie de la stigmergie: Essai d'interprétation du comportement des termites constructeurs , 1959, Insectes Sociaux.

[7]  Vincent Chevrier,et al.  Multi-agent simulation in biology: application to social spiders case , 2001 .

[8]  Bruce Edmonds,et al.  Making Self-Organising Adaptive Multiagent Systems Work , 2004 .

[9]  Chris Melhuish,et al.  Stigmergy, Self-Organization, and Sorting in Collective Robotics , 1999, Artificial Life.

[10]  Guy Theraulaz,et al.  Self-Organization in Biological Systems , 2001, Princeton studies in complexity.

[11]  Franco Zambonelli,et al.  Challenges and Research Directions in Agent-Oriented Software Engineering , 2004, Autonomous Agents and Multi-Agent Systems.

[12]  Vincent Chevrier,et al.  A new swarm mechanism based on social spiders colonies: From web weaving to region detection , 2003, Web Intell. Agent Syst..

[13]  E. Wilson The Insect Societies , 1974 .

[14]  Barbara Webb,et al.  Swarm Intelligence: From Natural to Artificial Systems , 2002, Connect. Sci..

[15]  Michael Luck,et al.  Methodologies and Software Engineering for Agent Systems , 2004, Multiagent Systems, Artificial Societies, and Simulated Organizations.

[16]  D. Chialvo,et al.  How Swarms Build Cognitive Maps , 1995 .

[17]  Maja J. Matarić,et al.  Dominance interactions, spatial dynamics and emergent reciprocity in a virtual world , 1996 .

[18]  Thomas D. Seeley,et al.  Adaptive significance of the age polyethism schedule in honeybee colonies , 1982, Behavioral Ecology and Sociobiology.

[19]  R. Jeanne,et al.  The organization of work in Polybia occidentalis: costs and benefits of specialization in a social wasp , 1986, Behavioral Ecology and Sociobiology.

[20]  Guy Theraulaz,et al.  Response Threshold Reinforcement and Division of Labor in Insect Societies , 1998 .

[21]  Massimo Cossentino,et al.  An Overview of Current Trends in European AOSE Research , 2005, Informatica.

[22]  C. Brooke Worth,et al.  The Insect Societies , 1973 .

[23]  Aude Billard,et al.  Hamelin: A model for collective adaptation based on internal stimuli , 2004 .