Abstract
The mathematical model of the biologically inspired, memetic, agentbased computation systems EMAS and iEMAS conformed to BDI (Belief Desire Intentions) standard is presented. The state of the systems and their dynamics are expressed as the stationary Markov chains. Such an approach allows for better understanding their complex behavior as well as their limitations. The contribution is concluded with selected experimental results obtained from the application of EMAS and iEMAS to the problem of global optimization for the popular benchmark functions and for computation-costly machine learning problems.
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Byrski, A., Schaefer, R. (2010). An Attempt to Stochastic Modeling of Memetic Systems. In: Sarker, R.A., Ray, T. (eds) Agent-Based Evolutionary Search. Adaptation, Learning, and Optimization, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13425-8_9
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DOI: https://doi.org/10.1007/978-3-642-13425-8_9
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