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dc.contributor.authorArkin, Ronald C.
dc.contributor.authorCervantes-Pérez, Francisco
dc.contributor.authorPeniche, José Francisco
dc.contributor.authorWeitzenfeld, Alfredo
dc.date.accessioned2008-05-14T16:24:48Z
dc.date.available2008-05-14T16:24:48Z
dc.date.issued1998
dc.identifier.urihttp://hdl.handle.net/1853/21583
dc.description.abstractAutonomous biological systems are very complex in their nature. Their study, through both experimentation and computation, provides a means to understand the underlying mechanisms in living systems while inspiring the development of technological applications. Experimentation, consisting of data gathering, generates predictions to be validated by experimentation on artificial systems. Computational models provide the understanding for the underlying dynamics, and serve as basis for simulation and further experimentation. The work presented here involves analyzing how predictive models can be generated from biological systems and then be used to drive robotic experiments; and conversely, how can results from robotic experiments drive additional neuroethological data gathering. This process requires a variety of visualization techniques in modeling and simulation of increasingly complex systems.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectAutonomous robotic systemsen_US
dc.subjectBehavior-based roboticsen_US
dc.subjectModeling biological systemsen_US
dc.subjectNeural networksen_US
dc.titleVisualization of Multi-Level Neural-Based Robotic Systemsen_US
dc.typeText
dc.contributor.corporatenameGeorgia Institute of Technology
dc.contributor.corporatenameInstituto Tecnológico Autónomo de México
dc.type.genrePaper


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  • Mobile Robot Laboratory [187]
    Papers, pre/post-prints, and presentations by faculty and students in the Georgia Tech Mobile Robot Laboratory.
  • Mobile Robot Laboratory Publications [187]
    Papers, pre/post-prints, and presentations by faculty and students in the Georgia Tech Mobile Robot Laboratory.

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