Furelos-Blanco D, Jonsson A. Solving Concurrent Multiagent Planning using Classical Planning. 6th Workshop on Distributed and Multi-Agent Planning (DMAP 2018)

In this work we present a novel approach to solving concurrent multiagent planning problems in which several agents act in parallel. Our approach relies on a compilation from concurrent multiagent planning to classical planning, allowing us to use an off-the-shelf classical planner to solve the original multiagent problem. The solution can be directly interpreted as a concurrent plan that satisfies a given set of concurrency constraints, while avoiding the exponential blowup associated with concurrent actions. Theoretically, we show that the compilation is sound and complete. Empirically, we show that our compilation can solve challenging multiagent planning problems that require concurrent actions.

Additional material

• The code of the compilation and the domains are available at the GitHub account of the AI-ML research group at UPF
• Open access version at UPF e-repository