TEXPLORE: Temporal Difference Reinforcement Learning for Robots and Time-Constrained Domains (Record no. 45448)
[ view plain ]
000 -LEADER | |
---|---|
fixed length control field | 03449nam a22005057a 4500 |
001 - CONTROL NUMBER | |
control field | sulb-eb0023356 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | BD-SySUS |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20160413122347.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
fixed length control field | cr nn 008mamaa |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 130623s2013 gw | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9783319011684 |
-- | 978-3-319-01168-4 |
024 7# - OTHER STANDARD IDENTIFIER | |
Standard number or code | 10.1007/978-3-319-01168-4 |
Source of number or code | doi |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
Classification number | Q342 |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | UYQ |
Source | bicssc |
Subject category code | COM004000 |
Source | bisacsh |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 006.3 |
Edition number | 23 |
100 1# - MAIN ENTRY--PERSONAL NAME | |
Personal name | Hester, Todd. |
Relator term | author. |
245 10 - TITLE STATEMENT | |
Title | TEXPLORE: Temporal Difference Reinforcement Learning for Robots and Time-Constrained Domains |
Medium | [electronic resource] / |
Statement of responsibility, etc. | by Todd Hester. |
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
Place of production, publication, distribution, manufacture | Heidelberg : |
Name of producer, publisher, distributor, manufacturer | Springer International Publishing : |
-- | Imprint: Springer, |
Date of production, publication, distribution, manufacture, or copyright notice | 2013. |
300 ## - PHYSICAL DESCRIPTION | |
Extent | XIV, 165 p. 55 illus. in color. |
Other physical details | online resource. |
336 ## - CONTENT TYPE | |
Content type term | text |
Content type code | txt |
Source | rdacontent |
337 ## - MEDIA TYPE | |
Media type term | computer |
Media type code | c |
Source | rdamedia |
338 ## - CARRIER TYPE | |
Carrier type term | online resource |
Carrier type code | cr |
Source | rdacarrier |
347 ## - DIGITAL FILE CHARACTERISTICS | |
File type | text file |
Encoding format | |
Source | rda |
490 1# - SERIES STATEMENT | |
Series statement | Studies in Computational Intelligence, |
International Standard Serial Number | 1860-949X ; |
Volume/sequential designation | 503 |
505 0# - FORMATTED CONTENTS NOTE | |
Formatted contents note | Introduction -- Background and Problem Specification -- Real Time Architecture -- The TEXPLORE Algorithm -- Empirical Evaluation -- Further Examination of Exploration -- Related Work -- Discussion and Conclusion -- TEXPLORE Pseudo-Code. |
520 ## - SUMMARY, ETC. | |
Summary, etc. | This book presents and develops new reinforcement learning methods that enable fast and robust learning on robots in real-time. Robots have the potential to solve many problems in society, because of their ability to work in dangerous places doing necessary jobs that no one wants or is able to do. One barrier to their widespread deployment is that they are mainly limited to tasks where it is possible to hand-program behaviors for every situation that may be encountered. For robots to meet their potential, they need methods that enable them to learn and adapt to novel situations that they were not programmed for. Reinforcement learning (RL) is a paradigm for learning sequential decision making processes and could solve the problems of learning and adaptation on robots. This book identifies four key challenges that must be addressed for an RL algorithm to be practical for robotic control tasks. These RL for Robotics Challenges are: 1) it must learn in very few samples; 2) it must learn in domains with continuous state features; 3) it must handle sensor and/or actuator delays; and 4) it should continually select actions in real time. This book focuses on addressing all four of these challenges. In particular, this book is focused on time-constrained domains where the first challenge is critically important. In these domains, the agent’s lifetime is not long enough for it to explore the domains thoroughly, and it must learn in very few samples. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Engineering. |
Topical term or geographic name as entry element | Image processing. |
Topical term or geographic name as entry element | Computational intelligence. |
Topical term or geographic name as entry element | Robotics. |
Topical term or geographic name as entry element | Automation. |
Topical term or geographic name as entry element | Engineering. |
Topical term or geographic name as entry element | Computational Intelligence. |
Topical term or geographic name as entry element | Image Processing and Computer Vision. |
Topical term or geographic name as entry element | Robotics and Automation. |
710 2# - ADDED ENTRY--CORPORATE NAME | |
Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY | |
Title | Springer eBooks |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Relationship information | Printed edition: |
International Standard Book Number | 9783319011677 |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
Uniform title | Studies in Computational Intelligence, |
International Standard Serial Number | 1860-949X ; |
Volume number/sequential designation | 503 |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | <a href="http://dx.doi.org/10.1007/978-3-319-01168-4">http://dx.doi.org/10.1007/978-3-319-01168-4</a> |
912 ## - | |
-- | ZDB-2-ENG |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Source of classification or shelving scheme | |
Koha item type |
No items available.