An excellent paper by Daniel Fišer "Lifted Fact-Alternating Mutex Groups and Pruned Grounding of Classical Planning Problems" was accepted to AAAI 2020. This means a great success for our research center because the AAAI (read tripple-AI) conference is one of the most renowned events for researchers and professionals in the field of artificial intelligence. It is organized by the Association for the Advancement of Artificial Intelligence (AAAI) and the 34th edition this year will take place on February 7-12, 2020 in New York, USA.
In this paper, we focus on the inference of mutex groups in the lifted (PDDL) representation. We formalize the inference and prove that the most commonly used translator from the Fast Downward (FD) planning system infers a certain subclass of mutex groups, called fact-alternating mutex groups (fam-groups). Based on that, we show that the previously proposed fam-groups-based pruning techniques for the STRIPS representation can be utilized during the grounding process with lifted fam-groups, i.e., before the full STRIPS representation is known. Furthermore, we propose an improved inference algorithm for lifted fam-groups that produces a richer set of fam-groups than the FD translator and we demonstrate a positive impact on the number of pruned operators and overall coverage. (Full paper)
DANIEL FIŠER, Planning group, Artificial Intelligence Center, 2019