Knowledge Engineering with Software Agents

Increasingly diverse and useful information repositories are being made available over the World Wide Web (Web). However, information retrieved from the Web is often of limited use for problem solving because it lacks task-relevance, structure and context. This research draws on software agency as a medium through which modeldriven knowledge engineering techniques can be applied to the Web. The IMPS (Internet-based Multi-agent Problem Solving) architecture described here involves software agents that can conduct structured on-line knowledge acquisition using distributed knowledge sources. Agent-generated domain ontologies are used to guide a flexible system of autonomous agents arranged in a server architecture. Generic problem solving methods developed within the expert system community supply structure and context.

[1]  M. R. Genesereth,et al.  Knowledge Interchange Format Version 3.0 Reference Manual , 1992, LICS 1992.

[2]  Dieter Fensel,et al.  Ontologies and the configurations of problem-solving methods , 1996 .

[3]  Nigel Shadbolt,et al.  A Tool to Support Living Ontologies , 1998 .

[4]  E. J. Friedman-hill,et al.  Jess, the Java expert system shell , 1997 .

[5]  Z E. Jess Friedman-hill,et al.  The Java Expert System Shell , 2000 .

[6]  Dieter Fensel.  An Ontology-based Broker: Making Problem-Solving Method Reuse Work , 1998 .

[7]  Dieter Fensel,et al.  Problem-solving methods in cyberspace , 1997, IJCAI 1997.

[8]  B. Chandrasekaran,et al.  Generic Tasks for Knowledge-Based Reasoning: The "Right" Level of Abstraction for Knowledge Acquisition , 1987, Int. J. Man Mach. Stud..

[9]  Walter Van de Velde.  Issues in knowledge level modelling , 1993 .

[10]  Henry Lieberman,et al.  Letizia: An Agent That Assists Web Browsing , 1995, IJCAI.

[11]  Giles,et al.  Searching the world wide Web , 1998, Science.

[12]  Alan H. Bond,et al.  Readings in Distributed Artificial Intelligence , 1988 .

[13]  George A. Miller,et al.  Introduction to WordNet: An On-line Lexical Database , 1990 .

[14]  Bob J. Wielinga,et al.  Using explicit ontologies in KBS development , 1997, Int. J. Hum. Comput. Stud..

[15]  Guus Schreiber,et al.  Towards a unification of knowledge modelling approaches , 1993 .

[16]  Michael Uschold,et al.  Knowledge level modelling: concepts and terminology , 1998, The Knowledge Engineering Review.

[17]  George A. Miller,et al.  Implementing a Lexical Network , 1990 .

[18]  Luc Steels,et al.  Components of Expertise , 1990, AI Mag..

[19]  Timothy W. Finin,et al.  KQML as an agent communication language , 1994, CIKM '94.

[20]  Luc Steels,et al.  Second-Generation Expert Systems , 1985, IEEE Expert.

[21]  Kevin Knight,et al.  Toward Distributed Use of Large-Scale Ontologies t , 1997 .

[22]  Nicholas R. Jennings,et al.  Towards a Cooperation Knowledge Level For Collaborative Problem Solving , 1992, ECAI.

[23]  Henrik Eriksson,et al.  Plug-and-Play: Construction of Task-Speci c Expert-System Shells Using Sharable Context Ontologies , 1996 .

[24]  Michael R. Genesereth,et al.  Software agents , 1994, CACM.

[25]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993, Knowl. Acquis..

[26]  Allen Newell,et al.  The Knowledge Level , 1989, Artif. Intell..

[27]  John McDermott,et al.  Usable and reusable programming constructs , 1991 .

[28]  Yolanda Gil,et al.  Explicit Representations of Problem-Solving Strategies to Support Knowledge Acquisition , 1996, AAAI/IAAI, Vol. 1.

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