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SteerBench: a benchmark suite for evaluating steering behaviors.

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Title: SteerBench: a benchmark suite for evaluating steering behaviors.
Authors: Singh, Shawn, Kapadia, Mubbasir, Faloutsos, Petros, Reinman, Glenn
Source: Computer Animation & Virtual Worlds. Sep-Dec2009, Vol. 20 Issue 5/6, p533-548. 16p.
Subjects: Virtual reality, Computational steering (Computer science), Benchmarking (Management), Intelligent agents, Algorithms, End users (Information technology)
Abstract: Steering is a challenging task, required by nearly all agents in virtual worlds. There is a large and growing number of approaches for steering, and it is becoming increasingly important to ask a fundamental question: how can we objectively compare steering algorithms? To our knowledge, there is no standard way of evaluating or comparing the quality of steering solutions. This paper presents SteerBench: a benchmark framework for objectively evaluating steering behaviors for virtual agents. We propose a diverse set of test cases, metrics of evaluation, and a scoring method that can be used to compare different steering algorithms. Our framework can be easily customized by a user to evaluate specific behaviors and new test cases. We demonstrate our benchmark process on two example steering algorithms, showing the insight gained from our metrics. We hope that this framework can grow into a standard for steering evaluation. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]
Copyright of Computer Animation & Virtual Worlds is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: <searchLink fieldCode="AR" term="%22Singh%2C+Shawn%22">Singh, Shawn</searchLink><br /><searchLink fieldCode="AR" term="%22Kapadia%2C+Mubbasir%22">Kapadia, Mubbasir</searchLink><br /><searchLink fieldCode="AR" term="%22Faloutsos%2C+Petros%22">Faloutsos, Petros</searchLink><br /><searchLink fieldCode="AR" term="%22Reinman%2C+Glenn%22">Reinman, Glenn</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Virtual+reality%22">Virtual reality</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+steering+%28Computer+science%29%22">Computational steering (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Benchmarking+%28Management%29%22">Benchmarking (Management)</searchLink><br /><searchLink fieldCode="DE" term="%22Intelligent+agents%22">Intelligent agents</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22End+users+%28Information+technology%29%22">End users (Information technology)</searchLink>
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  Data: Steering is a challenging task, required by nearly all agents in virtual worlds. There is a large and growing number of approaches for steering, and it is becoming increasingly important to ask a fundamental question: how can we objectively compare steering algorithms? To our knowledge, there is no standard way of evaluating or comparing the quality of steering solutions. This paper presents SteerBench: a benchmark framework for objectively evaluating steering behaviors for virtual agents. We propose a diverse set of test cases, metrics of evaluation, and a scoring method that can be used to compare different steering algorithms. Our framework can be easily customized by a user to evaluate specific behaviors and new test cases. We demonstrate our benchmark process on two example steering algorithms, showing the insight gained from our metrics. We hope that this framework can grow into a standard for steering evaluation. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Computer Animation & Virtual Worlds is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=44792580
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              Text: Sep-Dec2009
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