The Co-Evolutionary Algorithms and Intelligent Systems

  • June, Chung-Young (Robotics and Intelligent Information System Laboratory School of Electrical and Electronic Engineering, Chung-Ang University) ;
  • Byung, Jun-Hyo (Robotics and Intelligent Information System Laboratory School of Electrical and Electronic Engineering, Chung-Ang University) ;
  • Bo, Sim-Kwee (Robotics and Intelligent Information System Laboratory School of Electrical and Electronic Engineering, Chung-Ang University)
  • 발행 : 1998.10.01

초록

Simple Genetic Algorithm(SGA) proposed by J. H. Holland is a population-based optimization method based on the principle of the Darwinian natural selection. The theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. Although GA goes well in many applications as an optimization method, still it does not guarantee the convergence to a global optimum in some problems. In designing intelligent systems, specially, since there is no deterministic solution, a heuristic trial-and error procedure is usually used to determine the systems' parameters. As an alternative scheme, therefore, there is a growing interest in a co-evolutionary system, where two populations constantly interact and co-evolve. In this paper we review the existing co-evolutionary algorithms and propose co-evolutionary schemes designing intelligent systems according to the relation between the system's components.

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