Strategies to Improve Goal Selection in Satisficing Oversubscription Planning

Oversubscription planning (OSP) tackles the infeasibility of finding a plan that achieves all goals, due to a limited resource, typically a cost-bound. The objective is to discover a plan under this cost-bound that maximizes the utility. A leading-edge technique in satisficing OSP employs relaxed plans to estimate the cost of achieving goals and focuses planning efforts on goals deemed attainable based on this estimation. However, this approach faces two main challenges: the time required to calculate all estimations can result in no effective goal selection, and using relaxed plans often underestimates the real cost, leading to sets of oversubscribed goals. To address these challenges, our paper studies two solutions: computing the estimations only when needed and using real plans instead of relaxed plans to calculate cost estimations. Experiments show that real plans offer advantages in terms of initial plan utility, but the gap between both approaches narrows when more time is given for plan refinement.

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Publication Details

Journal
Proceedings of the International Conference on Automated Planning and Scheduling
Published
2025-09-16
DOI
https://doi.org/10.1609/icaps.v35i1.36122
Primary Topic
Complex Systems and Decision Making
Type
article
Field-Weighted Citation Impact
0.00

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article

Strategies to Improve Goal Selection in Satisficing Oversubscription Planning

Michael Barley, Patricia Riddle, Ángel García‐Olaya
Proceedings of the International Conference on Automated Planning and Scheduling
Complex Systems and Decision Making
article

Strategies to Improve Goal Selection in Satisficing Oversubscription Planning

Michael Barley, Patricia Riddle, Ángel García‐Olaya
article en

Abstract

Oversubscription planning (OSP) tackles the infeasibility of finding a plan that achieves all goals, due to a limited resource, typically a cost-bound. The objective is to discover a plan under this cost-bound that maximizes the utility. A leading-edge technique in satisficing OSP employs relaxed plans to estimate the cost of achieving goals and focuses planning efforts on goals deemed attainable based on this estimation. However, this approach faces two main challenges: the time required to calculate all estimations can result in no effective goal selection, and using relaxed plans often underestimates the real cost, leading to sets of oversubscribed goals. To address these challenges, our paper studies two solutions: computing the estimations only when needed and using real plans instead of relaxed plans to calculate cost estimations. Experiments show that real plans offer advantages in terms of initial plan utility, but the gap between both approaches narrows when more time is given for plan refinement.

Proceedings of the International Conference on Automated Planning and SchedulingVol. 35(1)
University of Auckland (NZ), Universidad Carlos III de Madrid (ES)
Universidad Carlos III de Madrid, European Regional Development Fund, Agencia Estatal de Investigación
Openalex Percentile: Top 71%
Complex Systems and Decision Making
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Strategies to Improve Goal Selection in Satisficing Oversubscription Planning — Michael Barley, Patricia Riddle, et al. · Proceedings of the International Conference on Automated Planning and Scheduling (2025) | TGRS Research Map | TGRS