UM
Residential Collegefalse
Status已發表Published
Multi-agent oriented constraint satisfaction
Liu J.; Jing H.; Tang Y.Y.
2002-03-01
Source PublicationARTIFICIAL INTELLIGENCE
ISSN0004-3702
Volume136Issue:1Pages:101-144
Abstract

This paper presents a multi-agent oriented method for solving CSPs (Constraint Satisfaction Problems). In this method, distributed agents represent variables and a two-dimensional grid-like environment in which the agents inhabit corresponds to the domains of the variables. Thus, the positions of the agents in such an environment constitute the solution to a CSP. In order to reach a solution state, the agents will rely on predefined local reactive behaviors; namely, better-move, least-move, and random-move. While presenting the formalisms and algorithm, we will analyze the correctness and complexity of the algorithm, and demonstrate the proposed method with two benchmark CSPs, i.e., n-queen problems and coloring problems. In order to further determine the effectiveness of different reactive behaviors, we will examine the performance of this method in deriving solutions based on behavior prioritization and different selection probabiities. © 2001 Published by Elsevier Science B.V.

KeywordBehavior Prioritization Behavior Selection Constraint Satisfaction Experimental Validation Multi-agent Reactive Moving Behaviors
DOI10.1016/S0004-3702(01)00174-6
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000174331300004
Scopus ID2-s2.0-0036498333
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionUniversity of Macau
AffiliationHong Kong Baptist University
Recommended Citation
GB/T 7714
Liu J.,Jing H.,Tang Y.Y.. Multi-agent oriented constraint satisfaction[J]. ARTIFICIAL INTELLIGENCE, 2002, 136(1), 101-144.
APA Liu J.., Jing H.., & Tang Y.Y. (2002). Multi-agent oriented constraint satisfaction. ARTIFICIAL INTELLIGENCE, 136(1), 101-144.
MLA Liu J.,et al."Multi-agent oriented constraint satisfaction".ARTIFICIAL INTELLIGENCE 136.1(2002):101-144.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Liu J.]'s Articles
[Jing H.]'s Articles
[Tang Y.Y.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Liu J.]'s Articles
[Jing H.]'s Articles
[Tang Y.Y.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Liu J.]'s Articles
[Jing H.]'s Articles
[Tang Y.Y.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.