國立虎尾科技大學 |

登入

回首頁

Adversarial Search and Spatial Reaso...

ProQuest Information and Learning Co.

Adversarial Search and Spatial Reasoning in Real Time Strategy Games.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Adversarial Search and Spatial Reasoning in Real Time Strategy Games./
作者:	Uriarte, Alberto.
面頁冊數:	1 online resource (125 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
Contained By:	Dissertation Abstracts International78-12B(E).
標題:	Computer science. -
電子資源:	click for full text (PQDT)
ISBN:	9780355080001

Adversarial Search and Spatial Reasoning in Real Time Strategy Games.
Uriarte, Alberto.

Adversarial Search and Spatial Reasoning in Real Time Strategy Games. - 1 online resource (125 pages)

Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.

Thesis (Ph.D.)--Drexel University, 2017.

Includes bibliographical references

For many years, Chess was the standard game to test new Artificial Intelligence (AI) algorithms for achieving robust game-playing agents capable of defeating the best human players. Nowadays, games like Go or Poker are used since they offer new challenges like larger state spaces, or non-determinism. Among these testbed games, Real-Time Strategy (RTS) games have raised as one of the most challenging. The unique properties of RTS games (simultaneous and durative actions, large state spaces, partial observability) make them a perfect scenario to test algorithms able to make decisions in dynamic and complex situations. This thesis makes a contribution towards achieving human-level AI in these complex games. Specifically, I focus on the problems of performing adversarial search in domains (1) with extremely large decision and state spaces, (2) where no forward model is available, and (3) the game state is partially observable. Additionally, I also study how spatial reasoning can be used to reduce the search space and to improve the RTS playing bots.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355080001Subjects--Topical Terms:

573171
Computer science.
Index Terms--Genre/Form:

554714
Electronic books.

Adversarial Search and Spatial Reasoning in Real Time Strategy Games.
LDR:02280ntm a2200337Ki 4500 001 916787
005 20180928111501.5
006 m o u
007 cr mn||||a|a||
008 190606s2017 xx obm 000 0 eng d
020 $a 9780355080001
035 $a (MiAaPQ)AAI10289603
035 $a (MiAaPQ)drexel:11026
035 $a AAI10289603
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Uriarte, Alberto. $3 1190624
245 1 0 $a Adversarial Search and Spatial Reasoning in Real Time Strategy Games.
264 0 $c 2017
300 $a 1 online resource (125 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
500 $a Adviser: Santiago Ontanon.
502 $a Thesis (Ph.D.)--Drexel University, 2017.
504 $a Includes bibliographical references
520 $a For many years, Chess was the standard game to test new Artificial Intelligence (AI) algorithms for achieving robust game-playing agents capable of defeating the best human players. Nowadays, games like Go or Poker are used since they offer new challenges like larger state spaces, or non-determinism. Among these testbed games, Real-Time Strategy (RTS) games have raised as one of the most challenging. The unique properties of RTS games (simultaneous and durative actions, large state spaces, partial observability) make them a perfect scenario to test algorithms able to make decisions in dynamic and complex situations. This thesis makes a contribution towards achieving human-level AI in these complex games. Specifically, I focus on the problems of performing adversarial search in domains (1) with extremely large decision and state spaces, (2) where no forward model is available, and (3) the game state is partially observable. Additionally, I also study how spatial reasoning can be used to reduce the search space and to improve the RTS playing bots.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Computer science. $3 573171
650 4 $a Artificial intelligence. $3 559380
655 7 $a Electronic books. $2 local $3 554714
690 $a 0984
690 $a 0800
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Drexel University. $b Computer Science. $3 1187050
773 0 $t Dissertation Abstracts International $g 78-12B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10289603 $z click for full text (PQDT)

筆 0 讀者評論

多媒體

評論

新增評論分享你的心得

Export

取書館別