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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Overview of the Control System.- Plan Representation for Robotic Agents.- Probabilistic Hybrid Action Models.- Learning Structured Reactive Navigation Plans.- Plan-Based Robotic Agents.- Conclusions.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Destinazione, tempi e costiDa: Ammareal, Morangis, Francia
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Da: CSG Onlinebuch GMBH, Darmstadt, Germania
Softcover. Condizione: 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. Codice articolo 18016
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Kartoniert / Broschiert. Condizione: 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 . Codice articolo 4877098
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Taschenbuch. Condizione: 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. Codice articolo 9783540003359
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Taschenbuch. Condizione: 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. Codice articolo 9783540003359
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Taschenbuch. Condizione: 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. Codice articolo 9783540003359
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