Research On The Coevolutionary Technique And Its Application

The researches on artificial neural networks, cellular automata andevolutionary computation characterized by self-organizing and self-learning andadaptation, rooting from simulating some natural phenomenon or the process,havebeen developed greatly as the science and technology entering the time when multidisciplines intercross, seeps mutually and affects mutually.The novel and important theory of biodiversity harmonious and cooperativeevolution has been the foundation of the bionomics and the sustainable developmentconcept.And coevolutionary algorithms have raised more and more attention fromresearchers recently, because it is more positive than Darwin's evolution theorywhich must take struggle for surviving as the central in the research on biologyevolution and the environmental protection, as well as instructing humanity'ssocial behavior.The evolutionary computation technique had been shown great potential andfar-reaching impact on design optimization, but it is far from realizing a systemof matching the human performance. In particular, in some innovation designapplications fields, such as construction, art, music, design, it is difficultto evaluate the fitness because the measure depends mainly on the human mind. Howthe system can provide the evolution opportunity for the individual at the sametime maximum avoid degenerating in the execution optimization process and mayrealize the intelligent fitness function have become the hot spot in the researchon computer-aided conceptual design.To solve the related questions, there has been specific contribution in thisarticle as follows:1. The proposed novel multi-individual cooperative reinforcement learningmodelReferring from the stimulus and suppression theory of neurons in the physiology,this paper has proposed a novel coevolutionary model-multi-individual cooperativereinforcement learning model.The model made individuals of low phenotypesuppressed and high phenotype reinforced by the relation of individual fitness.Sothe global phenotype accelerated upgrading to self-adapt the complexity of theecological environment.2. Research on the novel coevolutionary algorithm based on the cooperativereinforcement learning mechanismBy analyzing the biological development model in the ecosystem,the paper hasemphasized biological evolution combined congenital/hereditary feature andcompetitive learning.And based on the traditional genetic algorithm,the paper hasintroduced the cooperative reinforcement learning model.The new coevolutionaryalgorithm not only strengthened capacity of intelligent search but alsoaccelerated the convergency of the population.3. The application-test of the new coevolutionary algorithm in thecomputer-aided conceptual design(CACD)The paper has studied the application of the new coevolutionary algorithm inthe computer-aided conceptual design(CACD) based on combination Principle andcase-based reasoning mechanism. And the system has showed many constructionexamples of ingenious idea and innovative shape. Finally, the experiment resultsshowed the new algorithm has higher-performance characteristic than traditionalgenetic algorithm.A study is conducted on coevolutionary technique and its application incomputer-aided conceptual design(CACD) in this paper.It is hoped that it couldpromoted the development of the relate research fields.