國立虎尾科技大學 |

Goal-Based Agent Design : = Decision Making in General Game Playing.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Goal-Based Agent Design :/
Reminder of title:	Decision Making in General Game Playing.
Author:	Sheng, Xinxin.
Description:	1 online resource (180 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 73-05, Section: B, page: 3052.
Subject:	Computer science. -
Online resource:	click for full text (PQDT)
ISBN:	9781267176752

Goal-Based Agent Design : = Decision Making in General Game Playing.
Sheng, Xinxin.

Goal-Based Agent Design :Decision Making in General Game Playing. - 1 online resource (180 pages)

Source: Dissertation Abstracts International, Volume: 73-05, Section: B, page: 3052.

Thesis (Ph.D.)--North Carolina State University, 2011.

Includes bibliographical references

General Game Playing's primary research thrust is building automated intelligent computer agents that accept declarative descriptions of arbitrary games at run-time and are capable of using such descriptions to play effectively without human intervention. The research in general game playing approximates human cognitive processes, sophisticated planning, and problem solving with an instant reward system represented in games. General game playing has well-recognized research areas with diverse topics including knowledge representation, search, strategic planning, and machine learning. It attacks the general intelligence problem that Artificial Intelligence researchers have made little progress on for the last several decades. We have designed and implemented an automated goal-based general game playing agent that is capable of playing most games written in the Game Description Language and has shown excellent results for general-purpose learning in the general game playing environment. Our contributions include: the general game playing agent designed to play a wide variety of games, the knowledge reasoning performance improvement algorithm, the run-time feature identification algorithm, the contextual decision-making algorithm, and the GDL extension to enrich the game domain.

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

Mode of access: World Wide Web

ISBN: 9781267176752Subjects--Topical Terms:

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

554714
Electronic books.

Goal-Based Agent Design : = Decision Making in General Game Playing.
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500 $a Source: Dissertation Abstracts International, Volume: 73-05, Section: B, page: 3052.
500 $a Adviser: David Thuente.
502 $a Thesis (Ph.D.)--North Carolina State University, 2011.
504 $a Includes bibliographical references
520 $a General Game Playing's primary research thrust is building automated intelligent computer agents that accept declarative descriptions of arbitrary games at run-time and are capable of using such descriptions to play effectively without human intervention. The research in general game playing approximates human cognitive processes, sophisticated planning, and problem solving with an instant reward system represented in games. General game playing has well-recognized research areas with diverse topics including knowledge representation, search, strategic planning, and machine learning. It attacks the general intelligence problem that Artificial Intelligence researchers have made little progress on for the last several decades. We have designed and implemented an automated goal-based general game playing agent that is capable of playing most games written in the Game Description Language and has shown excellent results for general-purpose learning in the general game playing environment. Our contributions include: the general game playing agent designed to play a wide variety of games, the knowledge reasoning performance improvement algorithm, the run-time feature identification algorithm, the contextual decision-making algorithm, and the GDL extension to enrich the game domain.
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538 $a Mode of access: World Wide Web
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650 4 $a Computer engineering. $3 569006
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