Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Grounding symbols through evolutionary language games
Simulating the evolution of language
The Origins of Ontologies and Communication Conventions in Multi-Agent Systems
Autonomous Agents and Multi-Agent Systems
Infection-based self-configuration in agent societies
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
An Infection-Based Mechanism for Self-Adaptation in Multi-agent Complex Networks
SASO '08 Proceedings of the 2008 Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems
Convention emergence through spreading mechanisms
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Robust coordination in large convention spaces
AI Communications - European Workshop on Multi-Agent Systems (EUMAS) 2009
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Regulating the behavior of autonomous agents is necessary to solve coordination problems and minimize conflicts in multi-agent systems (MAS). It is well known that in practice centralized approaches are not viable to accomplish this. Thus, distributed regulating mechanisms, such as mechanisms for the emergence of social conventions, are highly needed. Nevertheless, existing studies have not focused on determining how the size of the convention space may influence the emergence of conventions. To that end in this paper we apply a mechanism for the distributed, dynamic emergence of social conventions, to a problem with a large convention space: finding a common vocabulary (lexicon) for the agents of a MAS that allows them to perfectly communicate with neither ambiguity nor inconsistencies. Therefore, we empirically show that the mechanism can cope with large convention spaces.