Corpus ID: 220793532

CAMPs: Learning Context-Specific Abstractions for Efficient Planning in Factored MDPs

@article{Chitnis2020CAMPsLC,
  title={CAMPs: Learning Context-Specific Abstractions for Efficient Planning in Factored MDPs},
  author={Rohan Chitnis and Tom Silver and Beomjoon Kim and Leslie Pack Kaelbling and Tomas Lozano-Perez},
  journal={ArXiv},
  year={2020},
  volume={abs/2007.13202}
}
Meta-planning, or learning to guide planning from experience, is a promising approach to improving the computational cost of planning. A general meta-planning strategy is to learn to impose constraints on the states considered and actions taken by the agent. We observe that (1) imposing a constraint can induce context-specific independences that render some aspects of the domain irrelevant, and (2) an agent can take advantage of this fact by imposing constraints on its own behavior. These… Expand

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