Counterfactual Reasoning in Automated Planning

Fuente: arXiv
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Autori principali: Pozanco, Alberto, Borrajo, Daniel, Veloso, Manuela
Natura: Preprint
Pubblicazione: 2026
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author Pozanco, Alberto
Borrajo, Daniel
Veloso, Manuela
author_facet Pozanco, Alberto
Borrajo, Daniel
Veloso, Manuela
contents Automated planning traditionally assumes that all aspects of a planning task (initial state, goals, and available actions) are fully specified in advance, an approach well-suited to domains with fixed rules and deterministic execution. However, real-world planning often requires flexibility, allowing for deviations from the original task parameters in response to unforeseen circumstances or to improve outcomes. This paper surveys existing works on counterfactual reasoning in automated planning, categorizing them by what elements are changed, when the reasoning is triggered, and why and how these changes are made. We conclude by discussing key findings and outlining open research questions to guide future work in this area.
format Preprint
id arxiv_https___arxiv_org_abs_2605_02603
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Counterfactual Reasoning in Automated Planning
Pozanco, Alberto
Borrajo, Daniel
Veloso, Manuela
Artificial Intelligence
Automated planning traditionally assumes that all aspects of a planning task (initial state, goals, and available actions) are fully specified in advance, an approach well-suited to domains with fixed rules and deterministic execution. However, real-world planning often requires flexibility, allowing for deviations from the original task parameters in response to unforeseen circumstances or to improve outcomes. This paper surveys existing works on counterfactual reasoning in automated planning, categorizing them by what elements are changed, when the reasoning is triggered, and why and how these changes are made. We conclude by discussing key findings and outlining open research questions to guide future work in this area.
title Counterfactual Reasoning in Automated Planning
topic Artificial Intelligence
url https://arxiv.org/abs/2605.02603