{'fraction_non_alphanumeric': 0.013729977116704805, 'fraction_numerical': 0.0, 'mean_word_length': 5.527363184079602, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Planning Via Petri Net Unfolding : Generalisation and Improvements

Recent research has connected automated planning and techniques for analysing reachability in Petri nets. One outcome is a new forward search approach to partial-order planning, based on translating planning problems into Petri nets and guiding a Petri net reachability technique called unfolding with planning heuristics. Unfolding is an attractive method for planning as it naturally enables the recognition and separate resolution of independent subproblems, and can be exponentially more efficient than state-space search. Unfortunately, existing requirements for the soundness and completeness of unfolding have confined the approach to the generation of optimal plans, given additive action costs and monotonic heuristics. In this paper, we establish a relaxation of these requirements under which we are able to generalise the unfolding technique to optimise non-additive criteria such as makespan, and to exploit inadmissible heuristics. This opens the way to using unfolding in the temporal and suboptimal planning settings. We also describe a number of improvements to the translation which reduce the size of the Petri net produced. Our experiments show that planning via unfolding is competitive across a range of problem settings.