KR2025Proceedings of the 22nd International Conference on Principles of Knowledge Representation and ReasoningProceedings of the 22nd International Conference on Principles of Knowledge Representation and Reasoning

Melbourne, Australia. November 11-17, 2025.

Edited by

ISSN: 2334-1033
ISBN: 978-1-956792-08-9

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Published by

Copyright © 2025 International Joint Conferences on Artificial Intelligence Organization

A Planning Compilation to Reason About Goal Achievement at Planning Time

  1. Alberto Pozanco(J.P. Morgan AI Research)
  2. Marianela Morales(J.P. Morgan AI Research)
  3. Daniel Borrajo(J.P. Morgan AI Research)
  4. Manuela Veloso(J.P. Morgan AI Research)

Keywords

  1. Classical Planning
  2. Task Reformulation
  3. Goal Commitment
  4. Goal Achievement

Abstract

Identifying the specific actions that achieve goals when

solving a planning task might be beneficial for various

planning applications. Traditionally, this identification occurs

post-search, as some actions may temporarily achieve goals

that are later undone and re-achieved by other actions. In

this paper, we propose a compilation that extends the

original planning task with commit actions that enforce the

persistence of specific goals once achieved, allowing

planners to identify permanent goal achievement during

planning. Experimental results indicate that solving the

reformulated tasks does not incur on any additional

overhead both when performing optimal and suboptimal

planning, while providing useful information for some

downstream tasks.