Visualizations for an Explainable Planning Agent

Tathagata Chakraborti, Kshitij P. Fadnis, Kartik Talamadupula, Mishal Dholakia, Biplav Srivastava, Jeffrey O. Kephart, Rachel K. E. Bellamy
2018 Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence  
In this demonstration, we report on the visualization capabilities of an Explainable AI Planning (XAIP) agent that can support human-in-the-loop decision-making. Imposing transparency and explainability requirements on such agents is crucial for establishing human trust and common ground with an end-to-end automated planning system. Visualizing the agent's internal decision making processes is a crucial step towards achieving this. This may include externalizing the "brain" of the agent:
more » ... g from its sensory inputs, to progressively higher order decisions made by it in order to drive its planning components. We demonstrate these functionalities in the context of a smart assistant in the Cognitive Environments Laboratory at IBM's T.J. Watson Research Center.
doi:10.24963/ijcai.2018/849 dblp:conf/ijcai/ChakrabortiFTDS18 fatcat:2en3wd3hqrahpcu3sphfkihrei