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Title: Explainable Planning Using Answer Set Programming
In human-aware planning problems, the planning agent may need to explain its plan to a human user, especially when the plan appears infeasible or suboptimal for the user. A popular approach to do so is called model reconciliation, where the planning agent tries to reconcile the differences between its model and the model of the user such that its plan is also feasible and optimal to the user. This problem can be viewed as an optimization problem, where the goal is to find a subset-minimal explanation that one can use to modify the model of the user such that the plan of the agent is also feasible and optimal to the user. This paper presents an algorithm for solving such problems using answer set programming.  more » « less
Award ID(s):
1812628
NSF-PAR ID:
10286658
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
International Conference on Principles of Knowledge Representation and Reasoning (
Volume:
17
Issue:
1
Page Range / eLocation ID:
662-666
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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