Abstract
A stationary Markov chain model of the agent-based computation system EMAS is presented. The primary goal of the model is better understanding the behavior of this class of systems as well as their constraints. The ergodicity of this chain can be verified for the particular case of EMAS, thus implying an asymptotic guarantee of success (the ability of finding all solutions of the global optimization problem). The presented model may be further adapted to numerous evolutionary and memetic systems.
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Byrski, A., Schaefer, R., Smołka, M., Cotta, C. (2010). Asymptotic Analysis of Computational Multi-Agent Systems. In: Schaefer, R., Cotta, C., Kołodziej, J., Rudolph, G. (eds) Parallel Problem Solving from Nature, PPSN XI. PPSN 2010. Lecture Notes in Computer Science, vol 6238. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15844-5_48
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DOI: https://doi.org/10.1007/978-3-642-15844-5_48
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