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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Taschenbuch. Zustand: 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. Artikel-Nr. 9783540003359
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Softcover. Zustand: 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. Artikel-Nr. 18016
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Taschenbuch. Zustand: Neu. Plan-Based Control of Robotic Agents | Improving the Capabilities of Autonomous Robots | Michael Beetz | Taschenbuch | xi | Englisch | 2002 | Springer | EAN 9783540003359 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Artikel-Nr. 102559191
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