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Plan-Based Control of Robotic Agents: Improving the Capabilities of Autonomous Robots: 2554 (Lecture Notes in Computer Science, 2554) - Softcover

 
9783540003359: Plan-Based Control of Robotic Agents: Improving the Capabilities of Autonomous Robots: 2554 (Lecture Notes in Computer Science, 2554)

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Robotic agents, such as autonomous office couriers or robot tourguides, must be both reliable and efficient. Thus, they have to flexibly interleave their tasks, exploit opportunities, quickly plan their course of action, and, if necessary, revise their intended activities.

This book makes three major contributions to improving the capabilities of robotic agents:

 - first, a plan representation method is introduced which allows for specifying flexible and reliable behavior

- second, probabilistic hybrid action models are presented as a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans

- third, the system XFRMLEARN capable of learning structured symbolic navigation plans is described in detail.

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Plan-Based Control of Robotic Agents Robotic agents, such as autonomous office couriers or robot tourguides, must be both reliable and efficient. Thus, they have to flexibly interleave their tasks, exploit opportunities, quickly plan their course of action, and, if necessary, revise their intended activities. This book makes three major contributions to improving the capabilities of robotic agents: - first, a plan representation method is introduced which allows for specifying flexible and reliable behavior - second, probabilistic hybrid action models are presented as a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans - third, the syst...

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9783662195024: Plan-Based Control of Robotic Agents: Improving the Capabilities of Autonomous Robots

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23 cm. original paperback. 192 pp. bibliography. "Lecture Notes in Computer Science". -(libr labels, library stamp, otherwise (very) good). 320g. Seller Inventory # 72088

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Softcover. Condition: Gut. Gebraucht - Gut Zustand: Gut, XI, 191 p. Also available online. About this book About this book Robotic agents, such as autonomous office couriers or robot tourguides, must be both reliable and efficient. Thus, they have to flexibly interleave their tasks, exploit opportunities, quickly plan their course of action, and, if necessary, revise their intended activities. This book makes three major contributions to improving the capabilities of robotic agents: - first, a plan representation method is introduced which allows for specifying flexible and reliable behavior - second, probabilistic hybrid action models are presented as a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans - third, the system XFRMLEARN capable of learning structured symbolic navigation plans is described in detail. Written for researchers and professionals. Seller Inventory # 18016

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Robotic agents, such as autonomous office couriers or robot tourguides, must be both reliable and efficient. Thus, they have to flexibly interleave their tasks, exploit opportunities, quickly plan their course of action, and, if necessary, revise their intended activities.This book makes three major contributions to improving the capabilities of robotic agents:- first, a plan representation method is introduced which allows for specifying flexible andreliable behavior - second, probabilistic hybrid action models are presented as a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans - third, the system XFRMLEARN capable of learning structured symbolic navigation plans is described in detail. 208 pp. Englisch. Seller Inventory # 9783540003359

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Robotic agents, such as autonomous office couriers or robot tourguides, must be both reliable and efficient. Thus, they have to flexibly interleave their tasks, exploit opportunities, quickly plan their course of action, and, if necessary, revise their intended activities.This book makes three major contributions to improving the capabilities of robotic agents:- first, a plan representation method is introduced which allows for specifying flexible andreliable behavior - second, probabilistic hybrid action models are presented as a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans - third, the system XFRMLEARN capable of learning structured symbolic navigation plans is described in detail. Seller Inventory # 9783540003359

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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Includes supplementary material: sn.pub/extrasRobotic agents, such as autonomous office couriers or robot tourguides, must be both reliable and efficient. Thus, they have to flexibly interleave their tasks, exploit opportunities, quickly plan . Seller Inventory # 4877098

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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Robotic agents, such as autonomous office couriers or robot tourguides, must be both reliable and efficient. Thus, they have to flexibly interleave their tasks, exploit opportunities, quickly plan their course of action, and, if necessary, revise their intended activities.This book makes three major contributions to improving the capabilities of robotic agents: first, a plan representation method is introduced which allows for specifying flexible and reliable behavior second, probabilistic hybrid action models are presented as a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans third, the system XFRMLEARN capable of learning structured symbolic navigation plans is described in detail.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 208 pp. Englisch. Seller Inventory # 9783540003359

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