A global optimality criterion for evolutionary computation
Jianqin Liu , Minjie Wei
Journal of Central South University ›› 1998, Vol. 5 ›› Issue (1) : 64 -67.
A global optimality criterion for evolutionary computation
Focussing on unification of concrete portions into a generic form of computational evolution, a generalized theoretical framework is necessary and imperative to be built to construct a universal computational theory of evolution machine. The NP problem solving capacity can be traced to the nature of meta-evolution mechanism with emergence features that determine corresponding homeostasis and diversity ranging in the domain of nonlinnear mapping from genotype to phenotype. In this paper a criterion that guarantees the global optimality of evolutionary computation process is proposed and proven rigorously. The global optimization criterion obtained is based on the non-parametric measarement for the whole evolution system and has great flexibility and evolvability. It leaves room for evolutionary system designing and developement. The formulization of the global description in statistical manifold space of information object family expresses evoluable evolutionary operator architecture and operation procedure in terms of evolution by evolution. The theoretical results are helpful to applications such as machine learning for automatic knowledge acquisition, pattern classification and recognition of complex images (e. q. OCR) and unsupervised system identification of nonlinear dynamical systems as well as chaos phenomena. The kernal of the formal system guided by global evolutionary optimization is proper to the implementation with object-oriented programming paradigm and abstract machine modelling.
evolutionary computation / artificial life / global optimization
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