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dc.contributor.advisorGerald Jay Sussman.en_US
dc.contributor.authorJacobi, Ian Campbellen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2014-02-10T13:33:10Z
dc.date.available2014-02-10T13:33:10Z
dc.date.issued2013en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/84718
dc.descriptionThesis (Elec. E. in Computer Science)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 105-107).en_US
dc.description.abstractWhile humans may solve problems by applying any one of a number of different problem solving strategies, computerized problem solving is typically brittle, limited in the number of available strategies and ways of combining them to solve a problem. In this thesis, I present a method to flexibly select and combine problem solving strategies by using a constraint-propagation network, informed by higher-order knowledge about goals and what is known, to selectively control the activity of underlying problem solvers. Knowledge within each problem solver as well as the constraint-propagation network are represented as a network of explicit propositions, each described with respect to five interrelated axes of concrete and abstract knowledge about each proposition. Knowledge within each axis is supported by a set of dependencies that allow for both the adjustment of belief based on modifying supports for solutions and the production of justifications of that belief. I show that this method may be used to solve a variety of real-world problems and provide meaningful justifications for solutions to these problems, including decision-making based on numerical evaluation of risk and the evaluation of whether or not a document may be legally sent to a recipient in accordance with a policy controlling its dissemination.en_US
dc.description.statementofresponsibilityby Ian Campbell Jacobi.en_US
dc.format.extent107 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleDynamic application of problem solving strategies : dependency-based flow controlen_US
dc.typeThesisen_US
dc.description.degreeElec.E.in Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc868670836en_US


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