國立高雄大學圖資館 |

Language: English

Back

Design of experiments for reinforcem...

Gatti, Christopher.

Design of experiments for reinforcement learning

Record Type:	Electronic resources : Monograph/item
Title/Author:	Design of experiments for reinforcement learningby Christopher Gatti.
Author:	Gatti, Christopher.
Published:	Cham :Springer International Publishing :2015.
Description:	xiii, 191 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Reinforcement learning.
Online resource:	http://dx.doi.org/10.1007/978-3-319-12197-0
ISBN:	9783319121970 (electronic bk.)

Design of experiments for reinforcement learning
Gatti, Christopher.

Design of experiments for reinforcement learning[electronic resource] /by Christopher Gatti. - Cham :Springer International Publishing :2015. - xiii, 191 p. :ill., digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

Introduction -- Reinforcement Learning. Design of Experiments -- Methodology -- The Mountain Car Problem -- The Truck Backer-Upper Problem -- The Tandem Truck Backer-Upper Problem -- Appendices.

This thesis takes an empirical approach to understanding of the behavior and interactions between the two main components of reinforcement learning: the learning algorithm and the functional representation of learned knowledge. The author approaches these entities using design of experiments not commonly employed to study machine learning methods. The results outlined in this work provide insight as to what enables and what has an effect on successful reinforcement learning implementations so that this learning method can be applied to more challenging problems.

ISBN: 9783319121970 (electronic bk.)

Standard No.: 10.1007/978-3-319-12197-0doiSubjects--Topical Terms:

349131
Reinforcement learning.

LC Class. No.: Q325.6 / .G388 2015

Dewey Class. No.: 006.31

Design of experiments for reinforcement learning
LDR:01732nmm a2200325 a 4500 001 460577
003 DE-He213
005 20150714145915.0
006 m d
007 cr nn 008maaau
008 151110s2015 gw s 0 eng d
020 $a 9783319121970 (electronic bk.)
020 $a 9783319121963 (paper)
024 7 $a 10.1007/978-3-319-12197-0 $2 doi
035 $a 978-3-319-12197-0
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.6 $b .G388 2015
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 006.31 $2 23
090 $a Q325.6 $b .G263 2015
100 1 $a Gatti, Christopher. $3 712098
245 1 0 $a Design of experiments for reinforcement learning $h [electronic resource] / $c by Christopher Gatti.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a xiii, 191 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer theses, $x 2190-5053
505 0 $a Introduction -- Reinforcement Learning. Design of Experiments -- Methodology -- The Mountain Car Problem -- The Truck Backer-Upper Problem -- The Tandem Truck Backer-Upper Problem -- Appendices.
520 $a This thesis takes an empirical approach to understanding of the behavior and interactions between the two main components of reinforcement learning: the learning algorithm and the functional representation of learned knowledge. The author approaches these entities using design of experiments not commonly employed to study machine learning methods. The results outlined in this work provide insight as to what enables and what has an effect on successful reinforcement learning implementations so that this learning method can be applied to more challenging problems.
650 0 $a Reinforcement learning. $3 349131
650 0 $a Artificial intelligence. $3 194058
650 1 4 $a Engineering. $3 210888
650 2 4 $a Computational Intelligence. $3 338479
650 2 4 $a Logic Design. $3 276275
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 252959
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Springer theses. $3 557607
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-12197-0
950 $a Engineering (Springer-11647)