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JACIII Vol.3 No.5 pp. 418-426
doi: 10.20965/jaciii.1999.p0418
(1999)

Paper:

Coevolutionary Algorithms for Realization of Intelligent Systems

Hyo-Byung Jun and Kwee-Bo Sim

Robotics and Intelligent Information System Laboratory School of Electrical and Electronic Engineering Chung-Ang University 221, Huksuk-Dong, Dongjak-Ku, Seou1156-756, Korea

Received:
December 14, 1998
Accepted:
July 5, 1999
Published:
October 20, 1999
Keywords:
Simple genetic algorithm, Schema theorem, Intelligent system, Co-evolutionary algorithm
Abstract

The simple genetic algorithm (SGA) proposed by J. H. Holland uses population-based optimization based on Darwinian natural selection. The theoretical foundations of GA are the Schema Theorem and Building Block Hypothesis. Although GA does well in many applications in optimization, it does not guarantee the convergence to a global optimum in some problems. In designing intelligent systems, since there is no deterministic solution, heuristic trial-and error is usually used to determine system parameters. An alternative is a coevolutionary system, where 2 populations constantly interact and coevolve. We review coevolutionary algorithms and propose coevolutionary schemes designing intelligent systems based on the relationship between system components.

Cite this article as:
Hyo-Byung Jun and Kwee-Bo Sim, “Coevolutionary Algorithms for Realization of Intelligent Systems,” J. Adv. Comput. Intell. Intell. Inform., Vol.3, No.5, pp. 418-426, 1999.
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