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dc.contributor.authorKapadia, Mubbasiren_US
dc.contributor.authorSingh, Shawnen_US
dc.contributor.authorAllen, Brianen_US
dc.contributor.authorReinman, Glennen_US
dc.contributor.authorFaloutsos, Petrosen_US
dc.contributor.editorEitan Grinspun and Jessica Hodginsen_US
dc.date.accessioned2016-02-18T11:50:49Z
dc.date.available2016-02-18T11:50:49Z
dc.date.issued2009en_US
dc.identifier.isbn978-1-60558-610-6en_US
dc.identifier.issn1727-5288en_US
dc.identifier.urihttp://dx.doi.org/10.1145/1599470.1599497en_US
dc.description.abstractThe size of crowds that modern computer games and urban simulations are capable of handling has given rise to the challenging problem of debugging and testing massive simulations of autonomous agents. In this paper, we propose SteerBug: an interactive framework for specifying and detecting steering behaviors. Our framework computes a set of time-varying metrics for agents and their environment, which characterize steering behaviors.We identify behaviors of interest by applying conditions (rules) or user defined sketches on the associated metrics. The behaviors we can specify and detect include unnatural steering, plainly incorrect results, or application-specific behaviors of interest. Our framework is extensible and independent of the specifics of any steering approach. To our knowledge, this is the first work that aims to provide a computational framework for specifying and detecting crowd behaviors in animation.en_US
dc.publisherACM SIGGRAPH / Eurographics Associationen_US
dc.subjectI.6.8 [Simulation and Modeling]en_US
dc.subjectTypes of SimulationAnimationen_US
dc.subjectI.2.11 [Artificial Intelligence]en_US
dc.subjectDistributed Artificial IntelligenceIntelligent Agentsen_US
dc.titleSteerBug: An Interactive Framework for Specifying and Detecting Steering Behaviorsen_US
dc.description.seriesinformationEurographics/ ACM SIGGRAPH Symposium on Computer Animationen_US
dc.description.sectionheadersCrowdsen_US
dc.identifier.doi10.1145/1599470.1599497en_US
dc.identifier.pages209-216en_US


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