mlsanityData to 14 Oct 2026

Towards Explainable AI Planning as a Service

arXiv 1908.05059 ↗First posted 14 Aug 2019cs.AIcited by 14

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Abstract (arXiv)

Explainable AI is an important area of research within which Explainable Planning is an emerging topic. In this paper, we argue that Explainable Planning can be designed as a service -- that is, as a wrapper around an existing planning system that utilises the existing planner to assist in answering contrastive questions. We introduce a prototype framework to facilitate this, along with some examples of how a planner can be used to address certain types of contrastive questions. We discuss the main advantages and limitations of such an approach and we identify open questions for Explainable Planning as a service that identify several possible research directions.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Aug 2019.

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Citing papers per year: 2021: 4; 2022: 2; 2023: 1; 2024: 1; 2025: 3; 2026: 3.

14 papers.

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  1. 2021Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Surveycited by 24
  2. 2021Seven challenges for harmonizing explainability requirementscited by 4
  3. 2022Policy Regularization for Legible Behaviorcited by 3
  4. 2023Explainable Goal Recognition: A Framework Based on Weight of Evidencecited by 3
  5. 2021Rule-based Shielding for Partially Observable Monte-Carlo Planningcited by 2
  6. 2022On Explainability in AI-Solutions: A Cross-Domain Surveycited by 2
  7. 2026Mind the Prompt: Self-adaptive Generation of Task Plan Explanations via LLMscited by 1
  8. 2021Actions You Can Handle: Dependent Types for AI Planscited by 0
  9. 2024Towards Probabilistic Planning of Explanations for Robot Navigationcited by 0
  10. 2025Counterfactual Explanations as Planscited by 0
  11. 2025What Questions Should Robots Be Able to Answer? A Dataset of User Questions for Explainable Roboticscited by 0
  12. 2025Informative Communication of Robot Planscited by 0
2 more
  1. 2026Contrastive explanations of BDI agentscited by 0
  2. 2026The Mirror Agent Model: a Bayesian Architecture for Interpretable Agent Behaviorcited by 0