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Rodney A. Brooks. Velásquez, Juan David Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2008-02-27T22:48:12Z 2008-02-27T22:48:12Z 2007 2007 http://hdl.handle.net/1721.1/40548 192097417 Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007. Includes bibliographical references (p. 245-262). This thesis presents a unified computational framework for the study of emotion that integrates several concepts and mechanisms which have been traditionally deemed to be integral components of intelligent behavior. We introduce the notion of affect programs as the primary theoretical constructs for investigating the function and the mechanisms of emotion, and instantiate these in a variety of embodied agents, including physical and simulated robots. Each of these affect programs establishes a functionally distinct mode of operation for the robots, that is activated when specific environmental contingencies are appraised. These modes involve the coordinated adjustment and entrainment of several different systems-including those governing perception, attention, motivation regulation, action selection, learning, and motor control-as part of the implementation of specialized solutions that take advantage of the regularities found in highly recurrent and prototypical environmental contingencies. We demonstrate this framework through multiple experimental scenarios that explore important features of the affect program abstraction and its function, including the demonstration of affective behavior, evaluative conditioning, incentive salience, and affective learning. by Juan David Velásquez. Ph.D. 262 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. When robots weep : a computational approach to affective learning Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="261a5ffe-cb68-4006-9d7b-c2915f22d32f"> <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>When robots weep : a computational approach to affective learning</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2007</PublicationDate> <Authors> <Author> <DisplayName>Velásquez, Juan David</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 presents a unified computational framework for the study of emotion that integrates several concepts and mechanisms which have been traditionally deemed to be integral components of intelligent behavior. We introduce the notion of affect programs as the primary theoretical constructs for investigating the function and the mechanisms of emotion, and instantiate these in a variety of embodied agents, including physical and simulated robots. Each of these affect programs establishes a functionally distinct mode of operation for the robots, that is activated when specific environmental contingencies are appraised. These modes involve the coordinated adjustment and entrainment of several different systems-including those governing perception, attention, motivation regulation, action selection, learning, and motor control-as part of the implementation of specialized solutions that take advantage of the regularities found in highly recurrent and prototypical environmental contingencies. We demonstrate this framework through multiple experimental scenarios that explore important features of the affect program abstraction and its function, including the demonstration of affective behavior, evaluative conditioning, incentive salience, and affective learning.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>