Learning as a Problem Solving Tool
| dc.contributor.author | Claybrook, Billy G. | en |
| dc.contributor.department | Computer Science | en |
| dc.date.accessioned | 2013-06-19T14:36:53Z | en |
| dc.date.available | 2013-06-19T14:36:53Z | en |
| dc.date.issued | 1974 | en |
| dc.description.abstract | This paper explores the use of learning as a practical tool in problem solving. The idea that learning should and eventually will be a vital component of most Artificial Intelligence programs is pursued. Current techniques in learning systems are compared. A detailed discussion of the problems of representing, modifying, and creating heuristics is given. Some of the questions asked (and answered) in the paper are: (1) how does the choice of representation affect the potential for learning?, (2) what techniques have been used to date and how do they compare?, i.e. first-order predicate calculus vs. production rules vs. Winston's representation, and (3) exactly how are heuristics modified in the existing systems and what do these techniques have in common? A discussion of the credit assignment problem as it relates to learning under the various schemes of representation is also presented. | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier | http://eprints.cs.vt.edu/archive/00000771/ | en |
| dc.identifier.sourceurl | http://eprints.cs.vt.edu/archive/00000771/01/CS74018-R.pdf | en |
| dc.identifier.trnumber | CS74018-R | en |
| dc.identifier.uri | http://hdl.handle.net/10919/20260 | en |
| dc.language.iso | en | en |
| dc.publisher | Department of Computer Science, Virginia Polytechnic Institute & State University | en |
| dc.relation.ispartof | Historical Collection(Till Dec 2001) | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.title | Learning as a Problem Solving Tool | en |
| dc.type | Technical report | en |
| dc.type.dcmitype | Text | en |
Files
Original bundle
1 - 1 of 1