Synthesizing Priority Planning Formulae for Multi-Agent Pathfinding

Shuwei Wang, Vadim Bulitko, Taoan Huang, Sven Koenig, Roni Stern

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Prioritized planning is a popular approach to multi-agent pathfinding. It prioritizes the agents and then repeatedly invokes a single-agent pathfinding algorithm for each agent such that it avoids the paths of higher-priority agents. Performance of prioritized planning depends critically on cleverly ordering the agents. Such an ordering is provided by a priority function. Recent work successfully used machine learning to automatically produce such a priority function given good orderings as the training data. In this paper we explore a different technique for synthesizing priority functions, namely program synthesis in the space of arithmetic formulae. We synthesize priority functions expressed as arithmetic formulae over a set of meaningful problem features via a genetic search in the space induced by a context-free grammar. Furthermore we regularize the fitness function by formula length to synthesize short, human-readable formulae. Such readability is an advantage over previous numeric machine-learning methods and may help explain the importance of features and how to combine them into a good priority function for a given domain. Moreover, our experimental results show that our formula-based priority functions outperform existing machine-learning methods on the standard benchmarks in terms of success rate, run time and solution quality without using more training data.

Original languageEnglish
Title of host publicationProceedings - AAAI Artificial Intelligence and Interactive Digital Entertainment Conference, AIIDE
EditorsMarkus Eger, Rogelio Enrique Cardona-Rivera
PublisherAssociation for the Advancement of Artificial Intelligence
Pages360-369
Number of pages10
Edition1
ISBN (Electronic)157735883X, 9781577358831
StatePublished - 6 Oct 2023
Event19th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2023 - Salt Lake City, United States
Duration: 8 Oct 202312 Oct 2023

Publication series

NameProceedings - AAAI Artificial Intelligence and Interactive Digital Entertainment Conference, AIIDE
Number1
Volume19
ISSN (Print)2326-909X
ISSN (Electronic)2334-0924

Conference

Conference19th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2023
Country/TerritoryUnited States
CitySalt Lake City
Period8/10/2312/10/23

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction
  • Software

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