Intelligent Farmer Agent for Multi-Agent Ecological Simulations Optimization

• Autor(es): Filipe Cruz ; António Pereira ; Pedro Valente ; Pedro Duarte ; Luis Paulo Reis
• Data: 2007
• Identificador Persistente: http://hdl.handle.net/10216/4553
• Origem: Repositório Aberto da Universidade do Porto
• Assunto(s): Ciência de computadores; Ciências Físicas; Cibernética; Inteligência artificial; Agentes inteligentes
• Tipo de Documento: Documento de conferência
• Idioma: Português

Descrição

This paper presents the development of a bivalve farmer agent interacting with a realistic ecological simulation system. The purpose of the farmer agent is to determine the best combinations of bivalve seeding areas in a large region, maximizing the production without exceeding the total allowed seeding area. A system based on simulated annealing, tabu search, genetic algorithms and reinforcement learning, was developed to minimize the number of iterations required to unravel a semi-optimum solution by using customizable tactics. The farmer agent is part of a multi-agent system where several agents, representing human interaction with the coastal ecosystems, communicate with a realistic simulator developed especially for aquatic ecological simulations. The experiments performed revealed promising results in the field of optimization techniques and multi-agent systems applied to ecological simulations. The results obtained open many other possible uses of the simulation architecture with applications in industrial and ecological management problems, towards sustainable development. This paper presents the development of a bivalve farmer agent interacting with a realistic ecological simulation system. The purpose of the farmer agent is to determine the best combinations of bivalve seeding areas in a large region, maximizing the production without exceeding the total allowed seeding area. A system based on simulated annealing, tabu search, genetic algorithms and reinforcement learning, was developed to minimize the number of iterations required to unravel a semi-optimum solution by using customizable tactics. The farmer agent is part of a multi-agent system where several agents, representing human interaction with the coastal ecosystems, communicate with a realistic simulator developed especially for aquatic ecological simulations. The experiments performed revealed promising results in the field of optimization techniques and multi-agent systems applied to ecological simulations. The results obtained open many other possible uses of the simulation architecture with applications in industrial and ecological management problems, towards sustainable development.