MAGR-BB matches exhaustive search accuracy on multi-agent Blocksworld while reducing hypothesis evaluations by orders of magnitude via RL scoring inside factorized branch-and-bound.
Recognizing multi-agent plans when action models and team plans are both incomplete
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Multi-Agent Goal Recognition with Team- and Goal-Conditioned Reinforcement Learning and Factorized Branch-and-Bound
MAGR-BB matches exhaustive search accuracy on multi-agent Blocksworld while reducing hypothesis evaluations by orders of magnitude via RL scoring inside factorized branch-and-bound.