Abstract
Cooperation as problem-solving and algorithm-design strategy is widely used to build methods addressing complex discrete optimization problems. In most cooperative-search algorithms, the explicit cooperation scheme yields a dynamic process not deliberately controlled by the algorithm design but inflecting the global behaviour of the cooperative solution strategy. The paper presents an overview of explicit cooperation mechanisms and describes issues related to the associated dynamic processes and the emergent computation they often generate. It also identifies a number of research directions into cooperation mechanisms, strategies for dynamic learning, automatic guidance, and self-adjustment, and the associated emergent computation processes.
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Crainic, T.G., Toulouse, M. (2008). Explicit and Emergent Cooperation Schemes for Search Algorithms. In: Maniezzo, V., Battiti, R., Watson, JP. (eds) Learning and Intelligent Optimization. LION 2007. Lecture Notes in Computer Science, vol 5313. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92695-5_8
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DOI: https://doi.org/10.1007/978-3-540-92695-5_8
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