2026-09-18T19:24:06Zhttps://dspace.mit.edu/server/oai/request

oai:dspace.mit.edu:1721.1/611412022-01-13T07:55:04Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023

Bruce M. Blumberg. Berlin, Matthew Roberts, 1980- Massachusetts Institute of Technology. Dept. of Architecture. Program In Media Arts and Sciences. Program in Media Arts and Sciences (Massachusetts Institute of Technology) 2011-02-23T14:19:20Z 2011-02-23T14:19:20Z 2003 2003 http://hdl.handle.net/1721.1/61141 54891918 Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2003. Includes bibliographical references (p. 63-65). The process of mammalian predatory sequence development offers a number of insights relevant to the goal of designing synthetic characters that can quickly and easily learn complicated and interesting behavior. We propose a number of principles for designing such learning systems, inspired by a targeted review of animal developmental phenomena, with particular emphasis on the development of predatory behavior in certain felid and canid species. We describe the implementation of a few of these principles as an extension to a popular algorithm for learning in autonomous systems called hierarchical Q-learning. In this new approach, the agent starts out with only one skill, and then new skills are added one at a time to its available repertoire as time passes. The agent is motivated to experiment thoroughly with each new skill as it is introduced. Simulation results are presented which empirically demonstrate the advantages of this new algorithm for the speed and effectiveness of the learning process. by Matthew Roberts Berlin. S.M. 65 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. Predatory sequence learning for synthetic characters Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="46f9582a-c02f-49ea-9e32-53c020596c4a"> <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>Predatory sequence learning for synthetic characters</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2003</PublicationDate> <Authors> <Author> <DisplayName>Berlin, Matthew Roberts, 1980-</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>The process of mammalian predatory sequence development offers a number of insights relevant to the goal of designing synthetic characters that can quickly and easily learn complicated and interesting behavior. We propose a number of principles for designing such learning systems, inspired by a targeted review of animal developmental phenomena, with particular emphasis on the development of predatory behavior in certain felid and canid species. We describe the implementation of a few of these principles as an extension to a popular algorithm for learning in autonomous systems called hierarchical Q-learning. In this new approach, the agent starts out with only one skill, and then new skills are added one at a time to its available repertoire as time passes. The agent is motivated to experiment thoroughly with each new skill as it is introduced. Simulation results are presented which empirically demonstrate the advantages of this new algorithm for the speed and effectiveness of the learning process.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>