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Situation agents: agent-based externalized steering logic.

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Title: Situation agents: agent-based externalized steering logic.
Authors: Schuerman, Matthew mschuerm@cs.ucla.edu, Singh, Shawn, Kapadia, Mubbasir, Faloutsos, Petros
Source: Computer Animation & Virtual Worlds. May2010, Vol. 21 Issue 3/4, p267-276. 10p. 6 Color Photographs.
Subjects: Computer simulation, Computational steering (Computer science), Computer-generated imagery, Computer graphics, Computer-aided design
Abstract: We present a simple and intuitive method for encapsulating part of agents' steering and coordinating abilities into a new class of agents, called situation agents. Situation agents have all the abilities of typical agents. In addition, they can influence the steering decisions of any agent, including other situation agents, within their sphere of influence. Encapsulating steering logic into moving agents is a powerful abstraction which provides more flexibility and efficiency than traditional informed environment approaches, and works with many of the current steering methodologies. We demonstrate our proposed approach in a number of challenging scenarios. Copyright © 2010 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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PubType: Academic Journal
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  Data: Situation agents: agent-based externalized steering logic.
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  Data: <searchLink fieldCode="AR" term="%22Schuerman%2C+Matthew%22">Schuerman, Matthew</searchLink><i> mschuerm@cs.ucla.edu</i><br /><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>
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  Data: <searchLink fieldCode="JN" term="%22Computer+Animation+%26+Virtual+Worlds%22">Computer Animation & Virtual Worlds</searchLink>. May2010, Vol. 21 Issue 3/4, p267-276. 10p. 6 Color Photographs.
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  Data: <searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+steering+%28Computer+science%29%22">Computational steering (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Computer-generated+imagery%22">Computer-generated imagery</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+graphics%22">Computer graphics</searchLink><br /><searchLink fieldCode="DE" term="%22Computer-aided+design%22">Computer-aided design</searchLink>
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  Data: We present a simple and intuitive method for encapsulating part of agents' steering and coordinating abilities into a new class of agents, called situation agents. Situation agents have all the abilities of typical agents. In addition, they can influence the steering decisions of any agent, including other situation agents, within their sphere of influence. Encapsulating steering logic into moving agents is a powerful abstraction which provides more flexibility and efficiency than traditional informed environment approaches, and works with many of the current steering methodologies. We demonstrate our proposed approach in a number of challenging scenarios. Copyright © 2010 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.)
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