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Regina Barzilay. Branavan, Satchuthananthavale Rasiah Kuhan Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2012-11-19T19:15:45Z 2012-11-19T19:15:45Z 2012 2012 http://hdl.handle.net/1721.1/74889 813960208 Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012. Cataloged from PDF version of thesis. Vita. Includes bibliographical references (p. 175-182). This thesis addresses the problem of grounding linguistic analysis in control applications, such as automated maintenance of computers and game playing. We assume access to natural language documents that describe the desired behavior of a control algorithm, either via explicit step-by-step instructions, via high-level strategy advice, or by specifying the dynamics of the control domain. Our goal is to develop techniques for automatically interpreting such documents, and leveraging the textual information to effectively guide control actions. We show that in this setting, langauge analysis can be learnt effectively via feedback signals inherent to the control application, obviating the need for manual annotations. Moreover we demonstrate how information automatically acquired from text can be used to improve the performance of the target control application. We apply our ideas to three applications of increasing linguistic and control complexity - interpreting step-by-step instructions into commands in a graphical user interface; interpreting high-level strategic advice to play a complex strategy game; and leveraging text descriptions of world dynamics to guide high-level planning. In all cases, our methods produce text analyses that agree with human notions of correctness, while yielding significant improvements over strong text-unaware methods in the target control application. by Satchuthananthavale Rasiah Kuhan Branavan. Ph.D. 182 p. eng Massachusetts Institute of Technology 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. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Grounding linguistic analysis in control applications Thesis application/pdf Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="cf67d08b-cabc-4c4d-a2d0-5c4cf22e66c4"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Grounding linguistic analysis in control applications</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2012</PublicationDate> <Authors> <Author> <DisplayName>Branavan, Satchuthananthavale Rasiah Kuhan</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>This thesis addresses the problem of grounding linguistic analysis in control applications, such as automated maintenance of computers and game playing. We assume access to natural language documents that describe the desired behavior of a control algorithm, either via explicit step-by-step instructions, via high-level strategy advice, or by specifying the dynamics of the control domain. Our goal is to develop techniques for automatically interpreting such documents, and leveraging the textual information to effectively guide control actions. We show that in this setting, langauge analysis can be learnt effectively via feedback signals inherent to the control application, obviating the need for manual annotations. Moreover we demonstrate how information automatically acquired from text can be used to improve the performance of the target control application. We apply our ideas to three applications of increasing linguistic and control complexity - interpreting step-by-step instructions into commands in a graphical user interface; interpreting high-level strategic advice to play a complex strategy game; and leveraging text descriptions of world dynamics to guide high-level planning. In all cases, our methods produce text analyses that agree with human notions of correctness, while yielding significant improvements over strong text-unaware methods in the target control application.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>