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Using Constraint Programming for Disjunctive Scheduling in Temporal AI Planning

Authors Adam Francis Green , J. Christopher Beck, Amanda Coles

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LIPIcs.CP.2024.12.pdf
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Subject Classification

ACM Subject Classification
  • Computing methodologies → Planning and scheduling
  • Theory of computation → Constraint and logic programming
  • Computing methodologies → Search methodologies
Keywords
  • AI Planning
  • Temporal-Numeric Planning
  • Constraint Programming
  • Scheduling

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Abstract

We present a novel scheduling model that leverages Constraint Programming (CP) to enhance problem solving performance in Temporal Planning. Building on the established strategy of decomposing causal and temporal reasoning, our approach abstracts two common fact structures present in many Temporal Planning problems - Semaphores and Envelopes - and performs temporal reasoning in a CP-based scheduler. At each search node in a heuristic search for a temporal plan, we construct and solve a Constraint Satisfaction Problem (CSP) and integrate feedback from the CP-based scheduler to guide the causal planning search towards a solution. Through experimental analysis, we validate the impact of these advances, demonstrating a significant reduction in both the number of states searched and in search time alongside an increase in problem-solving coverage.

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Adam Francis Green, J. Christopher Beck, and Amanda Coles. Using Constraint Programming for Disjunctive Scheduling in Temporal AI Planning. In 30th International Conference on Principles and Practice of Constraint Programming (CP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 307, pp. 12:1-12:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/LIPIcs.CP.2024.12

Author Details

Adam Francis Green
  • Department of Informatics, King’s College London, UK
  • Tango Hospitality Inc., Toronto, Canada
J. Christopher Beck
  • Department of Mechanical and Industrial Engineering, University of Toronto, Canada
Amanda Coles
  • Department of Informatics, King’s College London, UK

References

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