Making Believers out of Computers

Publisher Summary This chapter discusses the knowledge-based systems or KBS. The usual picture of logic is that it involves a expressive language, coupled with a sound and complete inference regime. On closer examination, the idea of a KBS is not totally vacuous. The idea is not just to construct systems that exhibit knowledge, but to represent that knowledge somehow in the data structures of the program, and to have the system perform whatever it is doing—diagnosing diseases, controlling a power plant, explaining its behaviour, or whatever—by manipulating that knowledge explicitly. Knowledge-based systems need to apply large amounts of knowledge. It must be possible at some level to apply knowledge without first requiring more knowledge to be applied at a higher level. Certain forms of knowledge are inherently intractable, and cannot be fully applied within reasonable resource bounds. A special kind of knowledge can be fully applied. The application of knowledge can also be made computationally tractable by making it logically unsound and incomplete in a principled way.

[1]  Hector J. Levesque,et al.  Krypton: A Functional Approach to Knowledge Representation , 1983, Computer.

[2]  K. Holyoak.  Mental representations. , 1982, Science.

[3]  Hector J. Levesque,et al.  Knowledge Level Interfaces to Information Systems , 1986, On Knowledge Base Management Systems.

[4]  Ronald Fagin,et al.  Belief, Awareness, and Limited Reasoning: Preliminary Report , 1985, IJCAI.

[5]  Nuel D. Belnap,et al.  Entailment : the logic of relevance and necessity , 1975 .

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

[7]  Hector J. Levesque,et al.  What Makes a Knowledge Base Knowledgeable? A View of Databases from the Knowledge Level , 1984, Expert Database Workshop.

[8]  H. Levesque.  A formal treatment of incomplete knowledge bases , 1981 .

[9]  Hector J. Levesque,et al.  KRYPTON: Integrating Terminology and Assertion , 1983, AAAI.

[10]  Hector J. Levesque,et al.  An Essential Hybrid Reasoning System: Knowledge and Symbol Level Accounts of KRYPTON , 1985, IJCAI.

[11]  Armin Haken,et al.  The Intractability of Resolution , 1985, Theor. Comput. Sci..

[12]  Raymond Reiter,et al.  A Logic for Default Reasoning , 1987, Artif. Intell..

[13]  Hector J. Levesque,et al.  The Tractability of Subsumption in Frame-Based Description Languages , 1984, AAAI.

[14]  Robert C. Moore.  Semantical Considerations on Nonmonotonic Logic , 1985, IJCAI.

[15]  Hector J. Levesque,et al.  A Logic of Implicit and Explicit Belief , 1984, AAAI.

[16]  Hector J. Levesque,et al.  Competence in Knowledge Representation , 1982, AAAI.

[17]  Hector J. Levesque,et al.  Foundations of a Functional Approach to Knowledge Representation , 1984, Artif. Intell..

[18]  Alan M. Frisch.  Using Model Theory to Specify AI Programs , 1985, IJCAI.

[19]  Joseph Y. Halpern,et al.  Towards a Theory of Knowledge and Ignorance: Preliminary Report , 1989, NMR.

[20]  Hector J. Levesque,et al.  The Interaction with Incomplete Knowledge Bases: A Formal Treatment , 1981, IJCAI.

[21]  Allen Newell.  The Knowledge Level (Presidential Address) , 1980, AI Mag..