Online planning for multi-agent systems with consensus protocol
Wenxu Zhang, Xiaolong Chen, Lei Ma · 2014
This article is concerned with decision-making and coordination among agents under uncertain conditions. We propose a novel algorithm for on-line planning of a multi-agent system based on Decentralized Partially Observable Markov Decision Processes (DEC-POMDP). This algorithm helps the multi-agent team to make a prudent decision in uncertain environment as prompt as possible. When communication is permitted, the agents exchange their partial information using a consensus protocol, such that the agents can approach a unique belief space. This guarantees that every agent makes a distributed decision which is the most beneficial to the team, unnecessary or false decisions are avoided. Furthermore, the algorithm can effectively reduce the agents' dependency on observation and historical information, computational complexity is also decreased. Simulation results show feasibility and validity of the proposed algorithm.