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GECCO
2005
Springer

Emergence of communication in competitive multi-agent systems: a pareto multi-objective approach

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Emergence of communication in competitive multi-agent systems: a pareto multi-objective approach
In this paper we investigate the emergence of communication in competitive multi-agent systems. A competitive environment is created with two teams of agents competing in an exploration task; the quickest team to explore the largest area wins. One team uses indirect communication and is controlled by an artificial neural network evolved using a Pareto multi-objective approach. The second team uses direct communication and a fixed strategy for exploration. A comparison is made between agents with and without communication. Results show that as the fitness function vary differing exploration strategies emerge. Experiments with communication produced cooperative strategies; while the experiments without communication produced effective strategies but with individuals acting independently. Categories and Subject Descriptors I.2.6 [Artificial Intelligence]: Learning - Concept learning Connectionism and neural nets General Terms Experimentation, Theory Keywords Communication, multi-agent sy...
Michelle McPartland, Stefano Nolfi, Hussein A. Abb
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where GECCO
Authors Michelle McPartland, Stefano Nolfi, Hussein A. Abbass
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