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Bruce M. Blumberg. Burke, Robert Carrington, 1976- Massachusetts Institute of Technology. Dept. of Architecture. Program In Media Arts and Sciences. Program in Media Arts and Sciences (Massachusetts Institute of Technology) 2011-02-23T14:15:53Z 2011-02-23T14:15:53Z 2001 2001 http://hdl.handle.net/1721.1/61119 50396924 Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2001. Includes bibliographical references (p. 91-93). Inspired by recent work in ethology and animal training, we integrate representations for time and rate into a behavior-based architecture for autonomous virtual creatures. The resulting computational model of affect and action selection allows these creatures to discover and refine their understanding of apparent temporal causality relationships which may or may not involve self-action. The fundamental action selection choice that a creature must make in order to satisfy its internal needs is whether to explore, react or exploit. In this architecture, that choice is informed by an understanding of apparent temporal causality, the representation for which is integrated into the representation for action. The ability to accommodate changing ideas about causality allows the creature to exist in and adapt to a dynamic world. Not only is such a model suitable for computational systems, but its derivation from biological models suggests that it may also be useful for gaining a new perspective on learning in biological systems. The implementation of a complete character built using this architecture is able to reproduce a variety of conditioning phenomena, as well as learn using a training technique used with live animals. by Robert Carrington Burke. S.M. 103 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 Architecture. Program In Media Arts and Sciences. It's about time : temporal representations for synthetic characters Temporal representations for synthetic characters Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="ecc33fba-0745-465c-8070-b2a3ca41e411"> <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>It&apos;s about time : temporal representations for synthetic characters</Title> <Subtitle>Temporal representations for synthetic characters</Subtitle> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2001</PublicationDate> <Authors> <Author> <DisplayName>Burke, Robert Carrington, 1976-</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>Architecture. Program In Media Arts and Sciences.</Keyword> <Abstract>Inspired by recent work in ethology and animal training, we integrate representations for time and rate into a behavior-based architecture for autonomous virtual creatures. The resulting computational model of affect and action selection allows these creatures to discover and refine their understanding of apparent temporal causality relationships which may or may not involve self-action. The fundamental action selection choice that a creature must make in order to satisfy its internal needs is whether to explore, react or exploit. In this architecture, that choice is informed by an understanding of apparent temporal causality, the representation for which is integrated into the representation for action. The ability to accommodate changing ideas about causality allows the creature to exist in and adapt to a dynamic world. Not only is such a model suitable for computational systems, but its derivation from biological models suggests that it may also be useful for gaining a new perspective on learning in biological systems. The implementation of a complete character built using this architecture is able to reproduce a variety of conditioning phenomena, as well as learn using a training technique used with live animals.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>