Abstract
A Markov chain model is proposed to describe the evolutionary dynamics of a multi-agent system. Many individual agents search for and exploit resources to get global optimization in an environment without complete information. With the selection acting on agent specialization at the level of system and under the condition of increasing returns, agent specialization emerges as the result of a long-term optimizing evolution.
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Chai, L., Chen, J., Han, Z., Di, Z., Fan, Y. (2007). Emergence of Specialization from Global Optimizing Evolution in a Multi-agent System. In: Shi, Y., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds) Computational Science – ICCS 2007. ICCS 2007. Lecture Notes in Computer Science, vol 4490. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72590-9_13
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