Explanation in second generation expert systems

What is needed for good explanation? This paper begins by considering some desiderata for expert system explanation. These desiderata concern not only the form and content of the explanations, but also the impact of explanation generation on the expert system itself— how it is built and how it performs. In this paper, we use these desiderata as a yardstick for measuring progress in the field. The paper describes two major developments that have differentiated explanation in second generation systems from explanation in first generation systems: 1) new architectures have been developed that capture more of the knowledge that is needed for explanation, and 2) more powerful explanation generators have been developed in which explanation generation is viewed as a problem-solving activity in its own right. These developments have led to significant improvements in explanation facilities: the explanations they offer are richer and more coherent, they are better adapted to the user’s needs and knowledge, and the explanation facilities can offer clarifying explanations to correct misunderstandings.

[1]  Kathleen R. McKeown.  Generating goal-oriented explanations , 1988 .

[2]  H. Grice.  Logic and conversation , 1975 .

[3]  H. C. Bunt,et al.  Modular incremental modelling of belief and intention , 1990 .

[4]  Michael C. Tanner,et al.  Explanations in knowledge systems: the roles of the task structure and domain functional models , 1991, IEEE Expert.

[5]  Daniel D. Suthers.  A task‐appropriate hybrid architecture for explanation , 1991 .

[6]  Kathleen McKeown,et al.  Discourse Strategies for Generating Natural-Language Text , 1985, Artif. Intell..

[7]  William R. Swartout,et al.  Explaining and Justifying Expert Consulting Programs , 1981, IJCAI.

[8]  Karen Sparck Jones.  Realism About User Modeling , 1989 .

[9]  Martha E. Pollack,et al.  A Model of Plan Inference That Distinguishes Between the Beliefs of Actors and Observers , 1986, ACL.

[10]  Derek H. Sleeman,et al.  UMFE: A User Modelling Front-End Subsystem , 1985, Int. J. Man Mach. Stud..

[11]  B. Chandrasekaran,et al.  Generic Tasks in Knowledge-Based Reasoning: High-Level Building Blocks for Expert System Design , 1986, IEEE Expert.

[12]  Alfred Kobsa.  Generating a User Model from Wh-Questions in the VIE-Lang System , 1983, GLDV-Jahrestagung.

[13]  William J. Clancey,et al.  The Epistemology of a Rule-Based Expert System - A Framework for Explanation , 1981, Artif. Intell..

[14]  Sandra Carberry,et al.  Plan Recognition in Natural Language Dialogue , 1990 .

[15]  B. Chandrasekaran,et al.  A Mechanism for Forming Composite Explanatory Hypotheses , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[16]  Johanna D. Moore,et al.  Enhanced Maintenance and Explanation of Expert Systems Through Explicit Models of Their Development , 1984, IEEE Transactions on Software Engineering.

[17]  William J. Clancey,et al.  The Advantages of Abstract Control Knowledge in Expert System Design , 1983, AAAI.

[18]  B. Chandrasekaran,et al.  Explaining control strategies in problem solving , 1989, IEEE Expert.

[19]  Bonnie L. Webber,et al.  Taking the Initiative in Natural Language Data Base Interactions: Justifying Why , 1982, COLING.

[20]  Jaime G. Carbonell,et al.  Learning the User’s Language: A Step Towards Automated Creation of User Models , 1989 .

[21]  William C. Mann.  An Overview of the Nigel Text Generation Grammar , 1983, ACL.

[22]  Edward H. Shortliffe,et al.  A rule-based computer program for advising physicians regarding antimicrobial therapy selection , 1974, ACM '74.

[23]  Johanna D. Moore,et al.  Explanations in knowledge systems: design for explainable expert systems , 1991, IEEE Expert.

[24]  Marlene Jones,et al.  Providing responses specific to a user's goals and background , 1989 .

[25]  H. Silverman.  A DIGITALIS THERAPY ADVISOR , 1975 .

[26]  Daniel D. Corkill,et al.  Selective Abstraction of AI System Activity , 1984, AAAI.

[27]  Penelope Sibun.  GENERATING TEXT WITHOUT TREES , 1992 .

[28]  David N. Chin.  Exploiting User Expertise in Answer Expression , 1988, AAAI.

[29]  Cécile Paris,et al.  Tailoring Object Descriptions to a User's Level of Expertise , 1988, Comput. Linguistics.

[30]  Peter van Beek,et al.  A Model For Generating Better Explanations , 1987, ACL.

[31]  William R. Swartout,et al.  XPLAIN: A System for Creating and Explaining Expert Consulting Programs , 1983, Artif. Intell..

[32]  William J. Clancey,et al.  Strategic Explanations for a Diagnostic Consultation System , 1983, Int. J. Man Mach. Stud..

[33]  William C. Mann,et al.  Rhetorical Structure Theory: Toward a functional theory of text organization , 1988 .

[34]  Martha E. Pollack,et al.  Inferring domain plans in question-answering , 1986 .

[35]  William J. Clancey,et al.  Heuristic Classification , 1986, Artif. Intell..

[36]  B. Chandrasekaran,et al.  Deep versus Compiled Knowledge Approaches to Diagnostic Problem-Solving , 1982, Int. J. Man Mach. Stud..

[37]  William C. Mann,et al.  An Overview of the Penman Text Generation System , 1983, AAAI.

[38]  Gerald Estrin,et al.  A reactive approach to explanation in expert and advice-giving systems , 1989 .

[39]  Johanna D. Moore.  Responding to :20HUH?”: answering vaguely articulated follow-up questions , 1989, CHI '89.

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

[41]  Joseph E. Grimes,et al.  The Thread of Discourse , 1984 .

[42]  Julia Hirschberg,et al.  User Participation in the Reasoning Processes of Expert Systems , 1982, AAAI.

[43]  Robert M. MacGregor,et al.  A Deductive Pattern Matcher , 1988, AAAI.

[44]  Alfred Kobsa,et al.  User Models in Dialog Systems , 1989, Symbolic Computation.

[45]  Gary S. Kahn,et al.  The Mud System , 1986, IEEE Expert.

[46]  J. Hobbs.  On the coherence and structure of discourse , 1985 .