語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Transferable strategic meta-reasonin...
~
Wunder, Michael.
Transferable strategic meta-reasoning models.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Transferable strategic meta-reasoning models./
作者:
Wunder, Michael.
面頁冊數:
1 online resource (243 pages)
附註:
Source: Dissertation Abstracts International, Volume: 75-04(E), Section: B.
標題:
Computer science. -
電子資源:
click for full text (PQDT)
ISBN:
9781303637827
Transferable strategic meta-reasoning models.
Wunder, Michael.
Transferable strategic meta-reasoning models.
- 1 online resource (243 pages)
Source: Dissertation Abstracts International, Volume: 75-04(E), Section: B.
Thesis (Ph.D.)--Rutgers The State University of New Jersey - New Brunswick, 2013.
Includes bibliographical references
How do strategic agents make decisions? For the first time, a confluence of advances in agent design, formation of massive online data sets of social behavior, and computational techniques have allowed for researchers to construct and learn much richer models than before. My central thesis is that, when agents engaged in repeated strategic interaction undertake a reasoning or learning process, the behavior resulting from this process can be characterized by two factors: depth of reasoning over base rules and time-horizon of planning. Values for these factors can be learned effectively from interaction and are transferable to new games, producing highly effective strategic responses. The dissertation formally presents a framework for addressing the problem of predicting a population's behavior using a meta-reasoning model containing these strategic components. To evaluate this model, I explore several experimental case studies that show how to use the framework to predict and respond to behavior using observed data, covering settings ranging from a small number of computer agents to a larger number of human participants.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9781303637827Subjects--Topical Terms:
573171
Computer science.
Index Terms--Genre/Form:
554714
Electronic books.
Transferable strategic meta-reasoning models.
LDR
:02311ntm a2200325K 4500
001
913727
005
20180622095236.5
006
m o u
007
cr mn||||a|a||
008
190606s2013 xx obm 000 0 eng d
020
$a
9781303637827
035
$a
(MiAaPQ)AAI3606606
035
$a
(MiAaPQ)rutgersnb:5012
035
$a
AAI3606606
040
$a
MiAaPQ
$b
eng
$c
MiAaPQ
100
1
$a
Wunder, Michael.
$3
1186682
245
1 0
$a
Transferable strategic meta-reasoning models.
264
0
$c
2013
300
$a
1 online resource (243 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: 75-04(E), Section: B.
500
$a
Adviser: Matthew Stone.
502
$a
Thesis (Ph.D.)--Rutgers The State University of New Jersey - New Brunswick, 2013.
504
$a
Includes bibliographical references
520
$a
How do strategic agents make decisions? For the first time, a confluence of advances in agent design, formation of massive online data sets of social behavior, and computational techniques have allowed for researchers to construct and learn much richer models than before. My central thesis is that, when agents engaged in repeated strategic interaction undertake a reasoning or learning process, the behavior resulting from this process can be characterized by two factors: depth of reasoning over base rules and time-horizon of planning. Values for these factors can be learned effectively from interaction and are transferable to new games, producing highly effective strategic responses. The dissertation formally presents a framework for addressing the problem of predicting a population's behavior using a meta-reasoning model containing these strategic components. To evaluate this model, I explore several experimental case studies that show how to use the framework to predict and respond to behavior using observed data, covering settings ranging from a small number of computer agents to a larger number of human participants.
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
Rutgers The State University of New Jersey - New Brunswick.
$b
Graduate School - New Brunswick.
$3
845606
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3606606
$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
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入