Solving Multiagent Planning Problems with Concurrent Conditional Effects
June 19, 2019 Β· Declared Dead Β· π AAAI Conference on Artificial Intelligence
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Authors
Daniel Furelos-Blanco, Anders Jonsson
arXiv ID
1906.08157
Category
cs.AI: Artificial Intelligence
Citations
3
Venue
AAAI Conference on Artificial Intelligence
Last Checked
4 months ago
Abstract
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. Our planner is the first to handle action effects that are conditional on what other agents are doing. 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.
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