Collection Path Ant Colony Optimization for Multi - agent Static Task Allocation ?

Mutual cooperation in Multi-Agent Systems is an important means to implement complex applications. The static task allocation is one of the key issues in agent cooperation mechanism. The latency of the network infrastructure, dynamic topology and node heterogeneity are important features of the agent system, and they bring new challenges to the static task allocation in multi-agent environment. Based on the traditional parallel computing task allocation method and Ant Colony Optimization algorithm, this paper proposes Collection Path Ant Colony Optimization, trying to find the globally optimal task allocation, and reduce the time complexity. We modify the heuristic function and the update strategy in the Ant-Cycle Model; establish three-dimensional path pheromone storage space. The experimental results on a multi-agent static task allocation show that CPACO is effective in system performance and reliability.