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

Towards Providing Explanations for AI Planner Decisions