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Barnyard politics : a decision rationale representation for the analysis of simple political situations

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dc.contributor.advisor Patrick H. Winston. en_US
dc.contributor.author Shahdadi, Arian, 1980- en_US
dc.contributor.other Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. en_US
dc.date.accessioned 2005-06-02T19:42:09Z
dc.date.available 2005-06-02T19:42:09Z
dc.date.copyright 2003 en_US
dc.date.issued 2003 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/18031
dc.description Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003. en_US
dc.description Includes bibliographical references (leaf 101). en_US
dc.description.abstract How can a computational system understand decisions in the domain of politics? In order to build computational systems that understand decisions in the abstract political space, we must first understand human decision-making and how human beings, in turn, are able to understand ideas in abstract realms such as politics. The work of Jintae Lee attempted to address the problem of understanding decision rationales in a non-domain specific way. His work falls short, however, when applied to decision problems in politics. I present a new representation, the Augmented Decision Rationale Language (ADRL) that attempts to address the shortcomings of Lee's work in this regard. ADRL expands Lee's vocabulary of relations to include forms of causation such as enablement and gating. ADRL also refines the relations and primitives of Lee's representation and focuses primarily on States, Actions and Goals as the basic units of decisions. Finally, ADRL grounds itself in spatial understanding using the Lexical Conceptual Semantics of Jackendoff, in contrast to the DRL, which ignores the text associated with a decision rationale. An implementation of a subset of this representation is displayed, along with a matcher that is able to create analogies between two decision scenarios cast in the representation. The matcher is presented an existence proof that this representation can be used to readily structure decision scenarios and make analogies between them. en_US
dc.description.statementofresponsibility by Arian Shahdadi. en_US
dc.format.extent 101 leaves en_US
dc.format.extent 4961843 bytes
dc.format.extent 4973671 bytes
dc.format.mimetype application/pdf
dc.format.mimetype application/pdf
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.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.uri http://dspace.mit.edu/handle/1721.1/7582
dc.subject Electrical Engineering and Computer Science. en_US
dc.title Barnyard politics : a decision rationale representation for the analysis of simple political situations en_US
dc.type Thesis en_US
dc.description.degree M.Eng. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. en_US
dc.identifier.oclc 57241319 en_US


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