DocumentCode
480804
Title
Negotiation in Semi-cooperative Agreement Problems
Author
Crawford, Elisabeth ; Veloso, Manuela
Author_Institution
Comput. Sci. Dept., Carnegie Mellon Univ., Pittsburgh, PA
Volume
2
fYear
2008
fDate
9-12 Dec. 2008
Firstpage
252
Lastpage
258
Abstract
In this paper we introduce the Semi-Cooperative Extended Incremental Multiagent Agreement Problem with Preferences (SC-EIMAPP). In SC-EIMAPPs, variables arise over time. For each variable, a set of distributed agents gain utility for agreeing on an option to assign to the variable. We define semi-cooperative utility as an agent´s privately owned preferences, discounted as negotiation time increases. SC-EIMAPPs reflect real world agreement problems, including meeting scheduling and task allocation.We analyze negotiation in SC-EIMAPPs theoretically. We note that agents necessarily reveal information about their own preferences and constraints as they negotiate agreements. We show how agents can use this limited and noisy information to learn to negotiate more effectively. We demonstrate our results experimentally.
Keywords
learning (artificial intelligence); multi-agent systems; scheduling; distributed agent gain utility; meeting scheduling; negotiation learning; semicooperative extended incremental multiagent agreement problem; task allocation; Bayesian methods; Collaboration; Computer science; Game theory; Humans; Intelligent agent; Meeting planning; Proposals; Protocols; USA Councils; Multiagent Learning; Negotiation;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
Conference_Location
Sydney, NSW
Print_ISBN
978-0-7695-3496-1
Type
conf
DOI
10.1109/WIIAT.2008.417
Filename
4740629
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