PRP Rebooted: Advancing the State of the Art in FOND Planning

Authors

  • Christian Muise Queen's University Vector Institute for Artificial Intelligence,
  • Sheila A. McIlraith University of Toronto Vector Institute for Artificial Intelligence,
  • J. Christopher Beck University of Toronto

DOI:

https://doi.org/10.1609/aaai.v38i18.30001

Keywords:

PRS: Planning under Uncertainty, SO: Heuristic Search

Abstract

Fully Observable Non-Deterministic (FOND) planning is a variant of classical symbolic planning in which actions are nondeterministic, with an action's outcome known only upon execution. It is a popular planning paradigm with applications ranging from robot planning to dialogue-agent design and reactive synthesis. Over the last 20 years, a number of approaches to FOND planning have emerged. In this work, we establish a new state of the art, following in the footsteps of some of the most powerful FOND planners to date. Our planner, PR2, decisively outperforms the four leading FOND planners, at times by a large margin, in 17 of 18 domains that represent a comprehensive benchmark suite. Ablation studies demonstrate the impact of various techniques we introduce, with the largest improvement coming from our novel FOND-aware heuristic.

Published

2024-03-24

How to Cite

Muise, C., McIlraith, S. A., & Beck, J. C. (2024). PRP Rebooted: Advancing the State of the Art in FOND Planning. Proceedings of the AAAI Conference on Artificial Intelligence, 38(18), 20212-20221. https://doi.org/10.1609/aaai.v38i18.30001

Issue

Section

AAAI Technical Track on Planning, Routing, and Scheduling