计算机科学 ›› 2010, Vol. 37 ›› Issue (9): 198-204.

• 人工智能 • 上一篇    下一篇

认知演化算法

王磊,王维平,杨峰,朱一凡   

  1. (国防科技大学信息系统与管理学院系统工程系 长沙410073)
  • 出版日期:2018-12-01 发布日期:2018-12-01

Cognition Evolutionary Algorithm

WANG Lei,WANG Wei-ping,YANG Feng,ZHU Yi-fan   

  • Online:2018-12-01 Published:2018-12-01

摘要: 受人类创造性思维过程的启发,借鉴认知心理学和创新计算的研究成果,提出了一种模拟人类基于创造性思维的问题求解过程和行为的智能算法—认知演化算法。该算法以知识为核心,将问题求解看成一个基于知识的创造性思维过程,对发散思维、收敛思维、记忆、执行、学习和价值体系6个关键模块进行了建模,充分发挥了知识演化和基于知识的创造性思维技巧在问题求解中的作用。通过数值实验分析了CEA各参数对算法性能的影响,并以一个扩展的路径优化问题将LEA与经典的智能算法进行了比较。实验结果表明,针对知识密集型优化问题,该算法能够以较少的目标评价次数得到问题的较优解。

关键词: 认知演化算法,创造性思维,问题求解,创新计算,认知心理学

Abstract: Inspired by the process of human creative thinking, cognition evolutionary algorithm, a novel intelligent algorithm based on cognition science and computational creativity, was proposed, which simulates the creative thinking based problem solving process and behaviors. The algorithm is comprised of six components which arc divergent thinking, convergent thinking, memory, execution, learning and value measures. Taking the problem-solving as a knowledge based creative thinking process,knowledge evolution and knowledge based creative thinking skills play important roles in the algorithm. I}he impact of the parameters of cognition evolutionary algorithm on the performance of the algorithm was analyzed through an extended path optimization problem. The results show that the novel algorithm can reduce object score evaluation times compared with other classic intelligent algorithms for solving knowledge intensive optimization problems.

Key words: Cognition evolutionary algorithm, Creative thinking, Problem solving, Computational creativity, Cognitive psychology

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