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Explainable planning using answer set programming

  • Van Nguyen
  • , Stylianos Loukas Vasileiou
  • , Tran Cao Son
  • , William Yeoh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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 subsetminimal 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.

Original languageEnglish
Title of host publication17th International Conference on Principles of Knowledge Representation and Reasoning, KR 2020
EditorsDiego Calvanese, Esra Erdem, Michael Thielscher
PublisherInternational Joint Conference on Artificial Intelligence (IJCAI)
Pages661-665
Number of pages5
ISBN (Electronic)9781713825982
StatePublished - 2020
Event17th International Conference on Principles of Knowledge Representation and Reasoning, KR 2020 - Rhodes, Greece
Duration: Sep 12 2020Sep 18 2020

Publication series

Name17th International Conference on Principles of Knowledge Representation and Reasoning, KR 2020
Volume2

Conference

Conference17th International Conference on Principles of Knowledge Representation and Reasoning, KR 2020
Country/TerritoryGreece
CityRhodes
Period09/12/2009/18/20

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