Counterfactual Reasoning in Automated Planning
For researchers in automated planning, this survey provides a structured overview of a nascent area, but it is incremental as it does not introduce new methods or results.
This paper surveys counterfactual reasoning in automated planning, categorizing existing works by what elements are changed, when reasoning is triggered, and why/how changes are made, concluding with open research questions.
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.