國立虎尾科技大學 |

A Concise Introduction to Decentralized POMDPs

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	A Concise Introduction to Decentralized POMDPs/ by Frans A. Oliehoek, Christopher Amato.
作者:	Oliehoek, Frans A.
其他作者:	Amato, Christopher.
面頁冊數:	XX, 134 p. 36 illus., 22 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Artificial intelligence. -
電子資源:	https://doi.org/10.1007/978-3-319-28929-8
ISBN:	9783319289298

A Concise Introduction to Decentralized POMDPs
Oliehoek, Frans A.

A Concise Introduction to Decentralized POMDPs[electronic resource] /by Frans A. Oliehoek, Christopher Amato. - 1st ed. 2016. - XX, 134 p. 36 illus., 22 illus. in color.online resource. - SpringerBriefs in Intelligent Systems, Artificial Intelligence, Multiagent Systems, and Cognitive Robotics,2196-548X. - SpringerBriefs in Intelligent Systems, Artificial Intelligence, Multiagent Systems, and Cognitive Robotics,.

Multiagent Systems Under Uncertainty -- The Decentralized POMDP Framework -- Finite-Horizon Dec-POMDPs -- Exact Finite-Horizon Planning Methods -- Approximate and Heuristic Finite-Horizon Planning Methods -- Infinite-Horizon Dec-POMDPs -- Infinite-Horizon Planning Methods: Discounted Cumulative Reward -- Infinite-Horizon Planning Methods: Average Reward -- Further Topics.

This book introduces multiagent planning under uncertainty as formalized by decentralized partially observable Markov decision processes (Dec-POMDPs). The intended audience is researchers and graduate students working in the fields of artificial intelligence related to sequential decision making: reinforcement learning, decision-theoretic planning for single agents, classical multiagent planning, decentralized control, and operations research. .

ISBN: 9783319289298

Standard No.: 10.1007/978-3-319-28929-8doiSubjects--Topical Terms:

559380
Artificial intelligence.

LC Class. No.: Q334-342

Dewey Class. No.: 006.3

A Concise Introduction to Decentralized POMDPs
LDR:02264nam a22003975i 4500 001 977802
003 DE-He213
005 20200701143812.0
007 cr nn 008mamaa
008 201211s2016 gw | s |||| 0|eng d
020 $a 9783319289298 $9 978-3-319-28929-8
024 7 $a 10.1007/978-3-319-28929-8 $2 doi
035 $a 978-3-319-28929-8
050 4 $a Q334-342
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
100 1 $a Oliehoek, Frans A. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1109994
245 1 2 $a A Concise Introduction to Decentralized POMDPs $h [electronic resource] / $c by Frans A. Oliehoek, Christopher Amato.
250 $a 1st ed. 2016.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a XX, 134 p. 36 illus., 22 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a SpringerBriefs in Intelligent Systems, Artificial Intelligence, Multiagent Systems, and Cognitive Robotics, $x 2196-548X
505 0 $a Multiagent Systems Under Uncertainty -- The Decentralized POMDP Framework -- Finite-Horizon Dec-POMDPs -- Exact Finite-Horizon Planning Methods -- Approximate and Heuristic Finite-Horizon Planning Methods -- Infinite-Horizon Dec-POMDPs -- Infinite-Horizon Planning Methods: Discounted Cumulative Reward -- Infinite-Horizon Planning Methods: Average Reward -- Further Topics.
520 $a This book introduces multiagent planning under uncertainty as formalized by decentralized partially observable Markov decision processes (Dec-POMDPs). The intended audience is researchers and graduate students working in the fields of artificial intelligence related to sequential decision making: reinforcement learning, decision-theoretic planning for single agents, classical multiagent planning, decentralized control, and operations research. .
650 0 $a Artificial intelligence. $3 559380
650 0 $a Control engineering. $3 1249728
650 0 $a Robotics. $3 561941
650 0 $a Mechatronics. $3 559133
650 0 $a Mathematical optimization. $3 527675
650 1 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Control, Robotics, Mechatronics. $3 768396
650 2 4 $a Optimization. $3 669174
700 1 $a Amato, Christopher. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1109995
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319289274
776 0 8 $i Printed edition: $z 9783319289281
830 0 $a SpringerBriefs in Intelligent Systems, Artificial Intelligence, Multiagent Systems, and Cognitive Robotics, $x 2196-548X $3 1260817
856 4 0 $u https://doi.org/10.1007/978-3-319-28929-8
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)