Emergent computation and the modeling and management of ecological systems

Abstract This paper introduces the emergent computational paradigm, discusses its applicability and potential in ecosystem management, and reviews the literature. Emergent computation is significantly different from the “classic” computational paradigm, where control is top-down and centralized. In emergent systems, overall system dynamics emerge from the local interactions of independent agents. In such systems, overall global control is minimized or eliminated altogether. Applications in ecosystem management include use of “artificial ecosystems” as surrogate experimental systems, and genetics-based machine learning systems to evolve management rule-sets for complex domains. Cellular automata, neural networks, genetic algorithms and classifier systems are discussed as examples of the emergent approach. Finally, an in-depth literature review of artificial ecosystems is provided.

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