Abstract
Automated negotiation has become increasingly important since the advent of electronic commerce. In an efficient market, goods are not necessarily traded in a fixed price, and instead buyers and sellers negotiate among themselves to reach a deal that maximizes the payoffs of both parties. In this paper, a genetic agent-based model for bilateral, multi-issue negotiation is studied. The negotiation agent employs genetic algorithms and attempts to learn its opponent’s preferences according to the history of the counter offers based upon the stochastic approximation. We also consider two types of agents: level- 0 agents are only concerned with their own interest while level-1 agents consider also their opponents’ utility. Our goal is to develop an automated negotiator that guides the negotiation process so as to maximize both parties’ payoff.
Original language | English |
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Title of host publication | Active Media Technology - 6th International Computer Science Conference, AMT 2001, Proceedings |
Editors | Jiming Liu, Pong C. Yuen, Chun-hung Li, Joseph Ng, Toru Ishida |
Publisher | Springer Verlag |
Pages | 224-234 |
Number of pages | 11 |
ISBN (Electronic) | 9783540430353 |
DOIs | |
Publication status | Published - 2001 |
Event | 6th International Computer Science Conference on Active Media Technology, AMT 2001 - Hong Kong, China Duration: 18 Dec 2001 → 20 Dec 2001 https://link.springer.com/book/10.1007/3-540-45336-9 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 2252 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 6th International Computer Science Conference on Active Media Technology, AMT 2001 |
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Country/Territory | China |
City | Hong Kong |
Period | 18/12/01 → 20/12/01 |
Internet address |
Scopus Subject Areas
- Theoretical Computer Science
- General Computer Science