Symmetry-Invariant Novelty Heuristics via Unsupervised Weisfeiler-Leman Features

Dillon Ze Chen

Track: Short Paper (5 pages including references)

Previous Publication: No, the submission has not been published or accepted at another conference.

Keywords: novelty heuristics, Weisfeiler Leman Features, heuristic search

Abstract: Novelty heuristics aid heuristic search by exploring states that exhibit novel atoms. However, novelty heuristics are not symmetry invariant and hence may sometimes lead to redundant exploration. In this preliminary report, we propose to use Weisfeiler-Leman Features for planning (WLFs) in place of atoms for detecting novelty. WLFs are recently introduced features for learning domain-dependent heuristics for generalised planning problems. We explore an unsupervised usage of WLFs for synthesising lifted, domain-independent novelty heuristics that are invariant to symmetric states. Experiments on the classical International Planning Competition and Hard To Ground benchmark suites yield promising results for novelty heuristics synthesised from WLFs.

Submission Number: 5