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dc.contributor.authorEldridge, Bryce D.
dc.contributor.authorMaciejewski, Anthony A.
dc.date.accessioned2015-07-28T20:36:11Z
dc.date.available2015-07-28T20:36:11Z
dc.date.issued2005
dc.descriptionIncludes bibliographical references.
dc.description.abstractThis paper expands on previous research on the effect of introducing social robots into crowded situations in order to improve pedestrian flow. In this case, a genetic algorithm is applied to find the optimal parameters for the interaction model between the robots and the people. Preliminary results indicate that adding social robots to a crowded situation can result in significant improvement in pedestrian flow. Using the optimized values of the model parameters as a guide, these robots can be designed to be more effective at improving the pedestrian flow. While this work only applies to one situation, the technique presented can be applied to a wide variety of scenarios.
dc.format.mediumborn digital
dc.format.mediumproceedings (reports)
dc.identifier.bibliographicCitationEldridge, Bryce D. and Anthony A. Maciejewski, Using Genetic Algorithms to Optimize Social Robot Behavior for Improved Pedestrian Flow, Proceedings: the International Conference on Systems, Man and Cybernetics, Waikoloa, Hawaii, October 10-12, 2005: 524-529.
dc.identifier.urihttp://hdl.handle.net/10217/1294
dc.languageEnglish
dc.publisherColorado State University. Libraries
dc.publisher.originalIEEE
dc.relation.ispartofFaculty Publications - Department of Electrical and Computer Engineering
dc.rights©2005 IEEE
dc.subjectcrowd dynamics
dc.subjectgenetic algorithms
dc.subjectsocial robots
dc.titleUsing genetic algorithms to optimize social robot behavior for improved pedestrian flow
dc.typeText


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