Modelo adaptativo para Organizaciones virtuales de agentes

[EN] An idea that seems to be gaining considerable ground is that modeling the interactions of a multi-agent system cannot be related exclusively to the actual agent and its communication capabilities, but must involve the use of concepts found in organizational engineering as well. It is possible t...

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Detalles Bibliográficos
Autor: Rodríguez González, Sara
Tipo de recurso: tesis doctoral
Fecha de publicación:2010
País:España
Institución:Universidad de Salamanca (USAL)
Repositorio:GREDOS. Repositorio Institucional de la Universidad de Salamanca
OAI Identifier:oai:gredos.usal.es:10366/76554
Acceso en línea:http://hdl.handle.net/10366/76554
Access Level:acceso abierto
Palabra clave:Tesis y disertaciones académicas
Universidad de Salamanca (España)
Tesis Doctoral
Academic dissertations
Inteligencia artificial
Artificial Intelligence
Ingeniería del software
Software engineering
1203.17 Informática
Descripción
Sumario:[EN] An idea that seems to be gaining considerable ground is that modeling the interactions of a multi-agent system cannot be related exclusively to the actual agent and its communication capabilities, but must involve the use of concepts found in organizational engineering as well. It is possible to establish different types of agent organizations according to the type of communication, the coordination among agents, and the type of agents that comprise the group. Each organization needs to be supported by a coordinated effort that explicitly determines how the agents should be organized and carry out the actions and tasks assigned to them. This thesis work presents a new global coordination model for an agent organization. The primary novelty of the model consists of the dynamic and adaptive planning capability to distribute tasks among the agent members of the organization as effectively as possible. This model is unique in its conception, allowing an organization in a highly dynamic environment to employ self-adaptive capabilities in execution time. This allows for the behavior of an agent to be determined by the goals it wishes to reach, while still giving consideration to the goals of other agents and any changes in the environment. The model is evaluated in a multi-agent system developed within an architecture oriented towards THOMAS organizations and simulated in a virtual environment.