Explaining Task Processing in Cognitive Assistants that Learn

As personal assistant software matures and assumes more autonomous control of its users’ 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 approach to explaining task reasoning. Key features include (1) an architecture designed for re-use among many different task execution systems; (2) a set of introspective predicates and a software wrapper that extract explanationrelevant 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 userfriendly explanations; and (4) a unified framework for explanation in which the task explanation system is integrated with previous work on explaining 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

[1]  William B. Thompson,et al.  Reconstructive Expert System Explanation , 1992, Artif. Intell..

[2]  Chris Mellish,et al.  Natural Language Generation from Plans , 1989, Comput. Linguistics.

[3]  Barbara Hayes-Roth,et al.  A Blackboard Architecture for Control , 1985, Artif. Intell..

[4]  Deborah L. McGuinness,et al.  Knowledge Provenance Infrastructure , 2003, IEEE Data Eng. Bull..

[5]  R. Michael Young,et al.  Using Grice's maxim of Quantity to select the content of plan descriptions , 1999, Artif. Intell..

[6]  Deborah L. McGuinness,et al.  IWTrust: Improving User Trust in Answers from the Web , 2005, iTrust.

[7]  Deborah L. McGuinness,et al.  A proof markup language for Semantic Web services , 2006, Inf. Syst..

[8]  Deborah L. McGuinness,et al.  Investigations into Trust for Collaborative Information Repositories: A Wikipedia Case Study , 2006, MTW.

[9]  Karen L. Myers.  Metatheoretic Plan Summarization and Comparison , 2006, ICAPS.

[10]  Deborah L. McGuinness,et al.  OWL Web ontology language overview , 2004 .

[11]  Anand S. Rao,et al.  BDI Agents: From Theory to Practice , 1995, ICMAS.

[12]  Deborah L. McGuinness,et al.  Explaining answers from the Semantic Web: the Inference Web approach , 2004, J. Web Semant..

[13]  Karen L. Myers,et al.  The SPARK agent framework , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

[14]  William J. Clancey,et al.  18 Methods for Generating Explanations , 2005 .

[15]  M. Rey.  Agents That Explain Their Own Actions , 1994 .