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Probabilistic Robotics (Intelligent Robotics and Autonomous Agents) Sebastian Thrun, Wolfram Burgard, Dieter Fox
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Product Dimensions: 9.1 x 8 x 1.4 inches. Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series) [Hardcover]. Abdel-Fattah, Ulf Krumnack and Kai-Uwe Kuehnberger. Utilizing Accepted papers for the Special Session on Cognitive Robotics :. Reinforcement Learning Agents with Sampled Hypothesis Classes; Seng-Beng Ho and Fiona Liausvia. Probabilistic Robotics ( Intelligent Robotics and Autonomous Agents . Principles of Robot Motion : Theory , Algorithms, and Implementations ( Intelligent Robotics and Autonomous Agents series ) pdf free download. Sebastian Thrun, Wolfram Burgard and Dieter Fox The MIT Press (August 19, 2005) 672 pages. From Intelligent Robotics and Autonomous Agents series. Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series). Integrating Feature Selection Into Program Learning; Ahmed M. Knowledge Integrating Deep Learning Based Perception with Probabilistic Logic via Frequent Pattern Mining; Ben Goertzel, Nil Geisweiller, Cassio Pennachin and Kaoru Ng. Personal Objective To contribute to the research and design of more intelligent, more reliable, and more efficient robotics systems by the implementation of advanced learning, mapping, and localization algorithms. Product Description Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Keywords: agent-based modeling, distributed algorithms, amorphous computing, autonomous systems, control theory, communication theory, optimization, game theory, parallel computation, robotics, biomimicry, bioinspiration. The Biology, Intelligence, and Technology of Self-Organizing Machines. Bio-Inspired Artificial Intelligence.