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. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Cruz, F., Pereira, A., Valente, P., Duarte, P., & Reis, L. P. (2007). Intelligent farmer agent for multi-agent ecological simulations optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4874 LNAI, pp. 593–604). Springer Verlag. https://doi.org/10.1007/978-3-540-77002-2_50
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