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.
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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.
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.
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Paperback. Condición: new. Paperback. 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. In recent years, autonomous robots, including Xavier, Martha [1], Rhino [2,3], Minerva,and Remote Agent, have shown impressive performance in long-term demonstrations. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783540001683
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