一种引入局部交互的群体协作行为协同进化机制

A Mechanism of Cooperative Coevolution with Local Interaction for Collective Cooperation Behaviors

现有协同进化模型在求解子系统间存在相互关联作用的问题时存在不足,使其难以高效产生群体复杂适应性协作行为.针对这一问题,依据系统论和非线性科学理论,构造了一种引入局部交互的群体复杂协作行为协同进化机制.该机制通过局部交互作用探测局部启发信息,并结合全局启发信息共同引导协同进化过程,从而使求解过程朝着正确的方向进化.算法分析及多机器人协作推箱实验表明,该机制模型及其算法有效地克服了现有协同进化模型的不足和局限,能使复杂关联的群体协作行为高效地朝着全局最优协作方向演化.

It is difficult for the existing models of cooperative coevolution to effectively produce collective complex adaptive cooperation behaviors because of their deficiency in solving problems with interaction between subsystems. In order to solve this problem, a new mechanism of cooperative coevolution with local interaction for collective complex cooperation behaviors is proposed based on system theory and nonlinear science theory. This mechanism leads the cooperative coevolution to the correct direction by combining global elicitation information with local elicitation information detected by local interaction. The algorithm analysis and simulation experiment of cooperative muhi-robot box-pushing show that this mechanism can effectively overcome the deficiency of the existing cooperative coevolution models, and can make the cooperation behaviors with complex correlation rapidly evolve to the global optimum solution.