Abstract
Search is among the most fundamental techniques for problem solving, and A* is probably the best known heuristic\nsearch algorithm. In this paper we adapt A* to the multiagent setting, focusing on multi-agent planning problems. We provide a simple formulation of multi-agent A*, with a parallel and distributed variant. Our algorithms exploit the structure of multi-agent problems to not only distribute the work efficiently among different agents, but also to remove symmetries and reduce the overall workload. Given a multi-agent\nplanning problem in which agents are not tightly coupled, our\nparallel version of A* leads to super-linear speedup, solving\nbenchmark problems that have not been solved before. In its\ndistributed version, the algorithm ensures that private information is not shared among agents, yet computation is still efficient – sometimes even more than centralized search – despite the fact that each agent has access to partial information only.
| Original language | American English |
|---|---|
| Title of host publication | Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems |
| Pages | 43-51 |
| Number of pages | 9 |
| Volume | 3 |
| State | Published - Jun 2012 |