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Probabilistic Reasoning and...
Probabilistic Reasoning and Decision Making in Sensory-Motor Systems by Pierre Bessiere, Christian Laugier and Roland Siegwart provides a unique collection of a sizable segment of the cognitive systems research community in Europe. It reports on contributions from leading academic institutions brought together within the European projects Bayesian Inspired Brain and Artifact (BIBA) and Bayesian Approach to Cognitive Systems (BACS). This fourteen-chapter volume covers important research along two main lines: new probabilistic models and algorithms for perception and action, new probabilistic methodology and techniques for artefact conception and development. The work addresses key issues concerned with Bayesian programming, navigation, filtering, modelling and mapping, with applications in a number of different contexts
Monografía
monografia Rebiun12639320 https://catalogo.rebiun.org/rebiun/record/Rebiun12639320 cr nn 008mamaa 100301s2008 gw | s |||| 0|eng d 9783540790075 978-3-540-79007-5 10.1007/978-3-540-79007-5 doi UPVA 996886872503706 UPM 991005576004904212 UAM 991007781128504211 UCAR 991007918478304213 CBUC 991004878679406711 UMO 69536 UPCT u359007 Bessiere, Pierre Probabilistic Reasoning and Decision Making in Sensory-Motor Systems Recurso electrónico-En línea] edited by Pierre Bessière, Christian Laugier, Roland Siegwart Berlin, Heidelberg Springer Berlin Heidelberg 2008 Berlin, Heidelberg Berlin, Heidelberg Springer Berlin Heidelberg XX, 378 P., 152 illus., Also available in online. digital XX, 378 P., 152 illus., Also available in online. Springer Tracts in Advanced Robotics 1610-7438 46 Engineering (Springer-11647) Part I Introduction -- Probability as an alternative to logic for rational sensory\2013 motor reasoning and decision -- Basic Concepts of Bayesian Programming -- Part II Robotics -- The CyCab: Bayesian navigation on sensory\2013motor Trajectories -- The Bayesian occupation filter -- Topological SLAM -- Probabilistic contextual situation analysis -- Bayesian Maps: probabilistic and hierarchical models for mobile robot navigation -- Bayesian approach to action selection and attention focusing -- Part III Industrial applications -- BCAD: a Bayesian CAD system for geometric problems specification and resolution -- 3D human hip volume reconstruction with incomplete multimodal medical images -- Playing to train your video game avatar -- Part IV Cognitive Modelling -- Bayesian modelling of visuo-vestibular interactions -- Bayesian modelling of perception of structure from motion -- Building a Talking Baby Robot: A contribution to the study of speech acquisition and evolution Accesible sólo para usuarios de la UPV Recurso a texto completo Probabilistic Reasoning and Decision Making in Sensory-Motor Systems by Pierre Bessiere, Christian Laugier and Roland Siegwart provides a unique collection of a sizable segment of the cognitive systems research community in Europe. It reports on contributions from leading academic institutions brought together within the European projects Bayesian Inspired Brain and Artifact (BIBA) and Bayesian Approach to Cognitive Systems (BACS). This fourteen-chapter volume covers important research along two main lines: new probabilistic models and algorithms for perception and action, new probabilistic methodology and techniques for artefact conception and development. The work addresses key issues concerned with Bayesian programming, navigation, filtering, modelling and mapping, with applications in a number of different contexts Reproducción electrónica Forma de acceso: Web Engineering Artificial intelligence Systems theory Engineering Automation and Robotics Artificial Intelligence (incl. Robotics) Control Engineering Systems Theory, Control Laugier, Christian Siegwart, Roland SpringerLink (Servicio en línea) Springer eBooks Springer eBooks Printed edition 9783540790068 Springer Tracts in Advanced Robotics 1610-7438 46