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. © Springer-Verlag Berlin Heidelberg 2007.
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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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4490 LNCS, pp. 98–105). Springer Verlag. https://doi.org/10.1007/978-3-540-72590-9_13
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