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Interactive hierarchical generate and test search.

dc.contributor.authorXu, Xin.
dc.date.accessioned2009-03-23T16:05:35Z
dc.date.available2009-03-23T16:05:35Z
dc.date.created1991
dc.date.issued1991
dc.degree.levelMasters
dc.degree.nameM.C.Sc.
dc.description.abstractMost of the search methods used in AI are inflexible. Interactive search is a new kind of search in which the search system can communicate and cooperate with external agents. There are two kinds of agents: human agents and non-human agents. Through interaction with human agents (man-machine interaction), the search system can make use of the human talent of judging the quality of a solution. Through interaction with non-human agents (machine-machine interaction), the search system can automatically exploit knowledge from its environment. An interactive search system has the ability to take advice from external agents. The ordinary non-interactive search models are the special instances of interactive search when the advice sequences are empty. We are investigating a particular kind of Interactive Search, IHGT (Interactive Hierarchical Generate and Test) search, which is established by introducing interactive ability into HGT (Hierarchical Generate and Test) search. To make HGT search interactive, we created an editor called GE (Generator Editor). GE was implemented in Prolog. GE is a bottom level language shell outside the HGT search model which translates advice into dynamic changes of all the three search factors. (Abstract shortened by UMI.)
dc.format.extent106 p.
dc.identifier.citationSource: Masters Abstracts International, Volume: 31-03, page: 1278.
dc.identifier.isbn9780315750265
dc.identifier.urihttp://hdl.handle.net/10393/7934
dc.identifier.urihttp://dx.doi.org/10.20381/ruor-7050
dc.publisherUniversity of Ottawa (Canada)
dc.subject.classificationArtificial Intelligence.
dc.titleInteractive hierarchical generate and test search.
dc.typeThesis

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