plan based control robotic agents di beetz michael (24 risultati)

Softcover. Condizione: Très bon. Ancien livre de bibliothèque. Edition 2008. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 2008. Ammareal gives back up to 15% of this item's net price to charity organizations.

Paperback. Condizione: Very Good. Ex-library paperback in very nice condition with the usual markings and attachments.

Taschenbuch. Condizione: Ausreichend. Aufl. 2002, Bibliotheksexemplar * Einband: leichte Gebrauchsspuren, Ecken angestoßen, abgerissener Aufkleber * Seiten: leichte Lesespuren.

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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.

Condizione: Gut. Gebraucht - Gut This book constitutes the thoroughly refereed post-proceedings of an international seminar on Plan-Based Control of Robotic Agents held at Dagstuhl Castle, Germany in October 2001.The 16 full papers included in the book have gone through two rounds of reviewing and revision and present an up-to-date survey of the state of the art on research in plan-based control of robotic agents. Besides general issues from robotics, agent systems, control, AI planning, algorithmic learning, and problem solving are plan-based high-level control, probabilistic reasoning, plan transformation, and resource adaptive reasoning key topics addressed in the papers. For Researchers and professionals.

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Taschenbuch. Condizione: Neu. Neuware -In recent years, autonomous robots, including Xavier, Martha [1], Rhino [2,3], Minerva,and Remote Agent, have shown impressive performance in long-term demonstrations. In NASA¿s Deep Space program, for example, an - tonomous spacecraft controller, called the Remote Agent [5], has autonomously performed a scienti c experiment in space. At Carnegie Mellon University, Xavier [6], another autonomous mobile robot, navigated through an o ce - vironment for more than a year, allowing people to issue navigation commands and monitor their execution via the Internet. In 1998, Minerva [7] acted for 13 days as a museum tourguide in the Smithsonian Museum, and led several thousand people through an exhibition. These autonomous robots have in common that they rely on plan-based c- trol in order to achieve better problem-solving competence. In the plan-based approach, robots generate control actions by maintaining and executing a plan that is e ective and has a high expected utility with respect to the robots¿ c- rent goals and beliefs. Plans are robot control programs that a robot can not only execute but also reason about and manipulate [4]. Thus, a plan-based c- troller is able to manage and adapt the robot¿s intended course of action ¿ the plan ¿ while executing it and can thereby better achieve complex and changing tasks. 304 pp. Englisch.

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.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - In recent years, autonomous robots, including Xavier, Martha [1], Rhino [2,3], Minerva,and Remote Agent, have shown impressive performance in long-term demonstrations. In NASA's Deep Space program, for example, an - tonomous spacecraft controller, called the Remote Agent [5], has autonomously performed a scienti c experiment in space. At Carnegie Mellon University, Xavier [6], another autonomous mobile robot, navigated through an o ce - vironment for more than a year, allowing people to issue navigation commands and monitor their execution via the Internet. In 1998, Minerva [7] acted for 13 days as a museum tourguide in the Smithsonian Museum, and led several thousand people through an exhibition. These autonomous robots have in common that they rely on plan-based c- trol in order to achieve better problem-solving competence. In the plan-based approach, robots generate control actions by maintaining and executing a plan that is e ective and has a high expected utility with respect to the robots' c- rent goals and beliefs. Plans are robot control programs that a robot can not only execute but also reason about and manipulate [4]. Thus, a plan-based c- troller is able to manage and adapt the robot's intended course of action - the plan - while executing it and can thereby better achieve complex and changing tasks.

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.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In recent years, autonomous robots, including Xavier, Martha [1], Rhino [2,3], Minerva,and Remote Agent, have shown impressive performance in long-term demonstrations. In NASA's Deep Space program, for example, an - tonomous spacecraft controller, called the Remote Agent [5], has autonomously performed a scienti c experiment in space. At Carnegie Mellon University, Xavier [6], another autonomous mobile robot, navigated through an o ce - vironment for more than a year, allowing people to issue navigation commands and monitor their execution via the Internet. In 1998, Minerva [7] acted for 13 days as a museum tourguide in the Smithsonian Museum, and led several thousand people through an exhibition. These autonomous robots have in common that they rely on plan-based c- trol in order to achieve better problem-solving competence. In the plan-based approach, robots generate control actions by maintaining and executing a plan that is e ective and has a high expected utility with respect to the robots' c- rent goals and beliefs. Plans are robot control programs that a robot can not only execute but also reason about and manipulate [4]. Thus, a plan-based c- troller is able to manage and adapt the robot's intended course of action - the plan - while executing it and can thereby better achieve complex and changing tasks. 304 pp. Englisch.

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 .

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.