Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
The AMAS theory for complex problem solving based on self-organizing cooperative agents
WETICE '03 Proceedings of the Twelfth International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises
A sample application of ADELFE focusing on analysis and design the mechanical synthesis problem
ESAW'04 Proceedings of the 5th international conference on Engineering Societies in the Agents World
Agent-oriented software patterns for rapid and affordable robot programming
Journal of Systems and Software
Towards an emergent taxonomy approach for adaptive profiling
SOCASE'08 Proceedings of the 2008 AAMAS international conference on Service-oriented computing: agents, semantics, and engineering
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The general aim of our work is to provide tools, methods and models to adaptive multi-agent systems designers. These systems consist in several interacting agents and have to optimize problem solving in a dynamic environment. In this context, the ADELFE method, which is based on a self-organizing adaptive multi-agent system model, was developed. Cooperation is used as a local criterion to self-organize the collective in order to reach functional adequacy with the environment. One key stage during the design process is to instantiate a cooperative agent model that is an extension to classical reactive models in which cooperation subsumes any other nominal behavior. A sample implementation of the agent model in the collective robotics domain – resource transportation – will illustrate a discussion on the model.