McCluskey, T.L. (1987) Combining weak learning heuristics in general problem solvers. In: 10th International Joint Conference on Artificial Intelligence, 1987, Milan, Italy.
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This paper is concerned with state space problem
solvers that achieve generality by learning strong
heuristics through experience in a particular domain. We specifically consider two ways of learning by analysing past solutions that can improve future problem solving: creating macros and the chunks. A method of learning search heuristics is specified which is related to 'chunking' but which complements the use
of macros within a goal directed system. An example of the creation and combined use of macros and chunks, taken from an implemented system, is described.
|Item Type:||Conference or Workshop Item (Paper)|
|Subjects:||Q Science > Q Science (General)|
T Technology > T Technology (General)
|Schools:||School of Computing and Engineering|
School of Computing and Engineering > Pedagogical Research Group
School of Computing and Engineering > Informatics Research Group
School of Computing and Engineering > Informatics Research Group > Knowledge Engineering and Intelligent Interfaces
|Depositing User:||Sharon Beastall|
|Date Deposited:||25 Jun 2010 08:46|
|Last Modified:||16 Dec 2010 13:58|
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