Plausibility-Based Heuristics for Latent Space Classical Planning

Yuta Takata; Alex Fukunaga

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arXiv · 2306.11434

Plausibility-Based Heuristics for Latent Space Classical Planning

Yuta Takata·Alex Fukunaga

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Abstract

Recent work on LatPlan has shown that it is possible to learn models for domain-independent classical planners from unlabeled image data. Although PDDL models acquired by LatPlan can be solved using standard PDDL planners, the resulting latent-space plan may be invalid with respect to the underlying, ground-truth domain (e.g., the latent-space plan may include hallucinatory/invalid states). We propose Plausibility-Based Heuristics, which are domain-independent plausibility metrics which can be computed for each state evaluated during search and uses as a heuristic function for best-first search. We show that PBH significantly increases the number of valid found plans on image-based tile puzzle and Towers of Hanoi domains.

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Yuta Takata, Alex Fukunaga. 2023-06-20. Plausibility-Based Heuristics for Latent Space Classical Planning. https://arxiv.org/abs/2306.11434

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