Towards Providing Explanations for AI Planner Decisions

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Borgo, Rita and Cashmore, Michael and Magazzeni, Daniele (2018) Towards Providing Explanations for AI Planner Decisions. In: IJCAI/ECAI 2018 Workshop on Explainable Artificial Intelligence (XAI), 2018-07-13 - 2018-07-13, Stockholmsmässan.

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Abstract

In order to engender trust in AI, humans must understand what an AI system is trying to achieve, and why. To overcome this problem, the underlying AI process must produce justifications and explanations that are both transparent and comprehensible to the user. AI Planning is well placed to be able to address this challenge. In this paper we present a methodology to provide initial explanations for the decisions made by the planner. Explanations are created by allowing the user to suggest alternative actions in plans and then compare the resulting plans with the one found by the planner. The methodology is implemented in the new XAI-Plan framework.

ORCID iDs

Borgo, Rita, Cashmore, Michael ORCID logoORCID: https://orcid.org/0000-0002-8334-4348 and Magazzeni, Daniele;
CORE (COnnecting REpositories)