Bilevel Planning with Learned Symbolic Abstractions from Interaction Data
Bilevel Planning with Learned Symbolic Abstractions from Interaction Data explores A bilevel neuro-symbolic framework for robot planning that combines learned probabilistic symbolic rules with continuous effect models for efficient and reliable plan generation and verification.. Commercial viability score: 7/10 in Robotics.
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