MODELING BEHAVIOR SEQUENCES: PRINCIPLES, PRACTICE, PROSPECTS

dc.contributor.authorWitten, Ian H.eng
dc.date.accessioned2008-02-27T22:26:04Z
dc.date.available2008-02-27T22:26:04Z
dc.date.computerscience1999-05-27eng
dc.date.issued1985-12-01eng
dc.description.abstractMany knowledge-based computer programs embody finite-state models which represent procedural knowledge, and use them to predict or interpret new observations. In accordance with prevailing methods of constructing expert systems, such models are invariably created by the knowledge engineer explicitly for the program's use. However, in most cases it would be of great practical (and theorectical) value if the program could infer models automatically from observations of behavior. This paper takes a wide-ranging look at the problems involved in building casual models of discrete sequences of symbols, and surveys methods of modeling. A key question for the future is the inference of goals and plans from observations of behavior, for procedural representations are much less flexible than the goal-oriented approach which people seem to favor. This issue is discussed and some speculations are included on how goals and plans might be inferred.eng
dc.description.notesWe are currently acquiring citations for the work deposited into this collection. We recognize the distribution rights of this item may have been assigned to another entity, other than the author(s) of the work.If you can provide the citation for this work or you think you own the distribution rights to this work please contact the Institutional Repository Administrator at digitize@ucalgary.caeng
dc.identifier.department1985-226-39eng
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/31167
dc.identifier.urihttp://hdl.handle.net/1880/46144
dc.language.isoEngeng
dc.publisher.corporateUniversity of Calgaryeng
dc.publisher.facultyScienceeng
dc.subjectComputer Scienceeng
dc.titleMODELING BEHAVIOR SEQUENCES: PRINCIPLES, PRACTICE, PROSPECTSeng
dc.typeunknown
thesis.degree.disciplineComputer Scienceeng
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