Explaining Task Processing in Cognitive Assistants that Learn.

Reference: McGuinness, D.L.; Glass, A.; Wolverton, M.; Pinheiro da Silva, P. Explaining Task Processing in Cognitive Assistants that Learn. Proceedings of the 20th International FLAIRS Conference (FLAIRS-20), Key West, Florida, May 7-9, 2007.

Abstract: As personal assistant software matures and assumes more autonomous control of user activities, it becomes more critical that this software can explain its task processing. It must be able to tell the user why it is doing what it is doing, and instill trust in the user that its task knowledge reflects standard practice and is being appropriately applied. We will describe the ICEE (Integrated Cognitive Explanation Environment) explanation system and its application to explaining task reasoning. Key features include (1) an architecture designed for re-use among different task execution systems; (2) a set of introspective predicates and a software wrapper that extract explanation-relevant information from a task execution system; (3) a version of the Inference Web explainer for generating formal justifications of task processing and converting them to user-friendly explanations; and (4) a unified framework for explaining results from task execution, learning, and deductive reasoning. Our work is focused on explaining belief-desire-intention (BDI) agent execution frameworks with the ability to learn. We demonstrate ICEE's application within CALO, a state-of-the-art personal software assistant, to explain the task reasoning of one such execution system and describe our associated trust study.


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