Resumen

TERAN, Juan; AGUILAR, José L  y  CERRADA, Mariela. Collective Learning in Multi-Agent Systems Based on Cultural Algorithms. CLEIej [online]. 2014, vol.17, n.2, pp.8-8. ISSN 0717-5000.

This paper aims to present a learning model for coordination schemes in Multi-Agent Systems (MAS) based on Cultural Algorithms (CA). In this model, the individuals (one of the CA components) are the different conversations that may occur in any multi-agent systems, and the coordination scheme learned is at the level of the way to perform the communication protocols into the conversation. A conversation can has sub-conversations, and the sub-conversations and/or conversations are identified with a particular type of conversation associated with a certain interaction patterns. The interaction patterns use the coordination mechanisms existing in the literature. In order to simulate the proposed learning model, we develop a computational tool called CLEMAS, which has been used to apply the model to a case of study in industrial automation, related to a Faults Management System based on Agents

Palabras clave : Cultural Algorithms; Coordination; Multi-Agent Systems.

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