Probabilistic reasoning and decision making in sensory-motor systems
Author(s)
Bibliographic Information
Probabilistic reasoning and decision making in sensory-motor systems
（Springer tracts in advanced robotics, v. 46）
Springer, c2008
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Description and Table of Contents
Description
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.
Table of Contents
Probability as an Alternative to Logic for Rational Sensory-Motor Reasoning and Decision.- Basic Concepts of Bayesian Programming.- Robotics.- The CyCab: Bayesian Navigation on Sensory-Motor 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.- 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.- 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.
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