Synthetic ethology and the evolution of cooperative communication
Adaptive Behavior
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Learning Sequential Decision Rules Using Simulation Models and Competition
Machine Learning - Special issue on genetic algorithms
Properties of the Bucket Brigade
Proceedings of the 1st International Conference on Genetic Algorithms
Be Patient and Tolerate Imprecision: How Autonomous Agents can Coordinate Effectively
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
A learning system based on genetic adaptive algorithms
A learning system based on genetic adaptive algorithms
A Mathematical Theory of Communication
A Mathematical Theory of Communication
Classifier fitness based on accuracy
Evolutionary Computation
An evidential and genetic method for cooperative learning systems
Multiagent and Grid Systems
An evidential cooperative multi-agent system
Expert Systems with Applications: An International Journal
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Classifier systems are rule-based systems dedicated to the learning of more or less complex tasks. They evolve toward a solution without any external help.When the problem is very intricate it is useful to have different systems, each of them being in charge with an easier part of the problem. The set of all the entities responsible for the resolution of each sub-task, forms a multi-agent system. Agents have to learn how to exchange information in order to solve the main problem. In this paper, we define the minimal requirements needed by a multi-agent classifier system to evolve communication. We thus design a minimal model involving two classifier systems which goal is to communicate with each other. A measure of entropy that evaluates the emergence of a common referent between agents has been finalised. Promising results let think that this work is only the beginning of our ongoing research activity.