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Analysis of cluster formations on planer cells based on genetic programming

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  • Jianjun Lu

    (China Agricultural University)

  • Shozo Tokinaga

    (Kyushu University)

Abstract

This paper offers an analysis of cluster formations on planer cells comprised of multi-agents utilizing local interactions and state transitions based on Genetic Programming (GP) and its applications. First, we illustrate that if the states of agents are allowed to have continuous values, equilibrium is attained on the basis of the fixed-point theorem. We also show that if the agents are restricted to binary states, equilibrium is attained in an asymptotic sense. However, for agents characterized by more than one state, the attainment of equilibrium is not ensured. We examine our results by using a simulation wherein agents learn from past experiences based on GP. Finally, we demonstrate a system comprised of cluster formations on planer cells comprised of artificial agents, and apply this system to the clustering of employees in firms.

Suggested Citation

  • Jianjun Lu & Shozo Tokinaga, 2013. "Analysis of cluster formations on planer cells based on genetic programming," Computational and Mathematical Organization Theory, Springer, vol. 19(4), pages 426-445, December.
    • Handle: RePEc:spr:comaot:v:19:y:2013:i:4:d:10.1007_s10588-012-9112-3
    DOI: 10.1007/s10588-012-9112-3
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    Cited by:

    1. Jianjun Lu & Shozo Tokinaga, 2016. "Cluster fluctuation in two-dimensional lattices with local interactions," Computational and Mathematical Organization Theory, Springer, vol. 22(2), pages 237-259, June.
    2. Lu, Jianjun & Tokinaga, Shozo, 2014. "Estimation of state changes in system descriptions for dynamic Bayesian networks by using a genetic procedure and particle filters," Economic Modelling, Elsevier, vol. 39(C), pages 138-145.

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