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Plan-Based Control of Robotic Agents : Improving the Capabilities of Autonomous Robots / by Michael Beetz.

SpringerLink Books Lecture Notes In Computer Science (LNCS) (1997-2024) Available online

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Format:
Book
Author/Creator:
Beetz, Michael, author.
Contributor:
SpringerLink (Online service)
Series:
Computer Science (Springer-11645)
Lecture notes in computer science. Lecture notes in artificial intelligence ; 2554.
Lecture Notes in Artificial Intelligence ; 2554
Language:
English
Subjects (All):
Robotics.
Automation.
Artificial intelligence.
Computer science.
Computer networks.
Computers, Special purpose.
Automatic control.
Mechatronics.
Robotics and Automation.
Artificial Intelligence.
Computer Science, general.
Computer Communication Networks.
Special Purpose and Application-Based Systems.
Control, Robotics, Mechatronics.
Local Subjects:
Robotics and Automation.
Artificial Intelligence.
Computer Science, general.
Computer Communication Networks.
Special Purpose and Application-Based Systems.
Control, Robotics, Mechatronics.
Physical Description:
1 online resource (XI, 194 pages).
Edition:
First edition 2002.
Contained In:
Springer eBooks
Place of Publication:
Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2002.
System Details:
text file PDF
Summary:
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.
Contents:
Overview of the Control System
Plan Representation for Robotic Agents
Probabilistic Hybrid Action Models
Learning Structured Reactive Navigation Plans
Plan-Based Robotic Agents
Conclusions.
Other Format:
Printed edition:
ISBN:
978-3-540-36381-1
9783540363811
Access Restriction:
Restricted for use by site license.

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