@inproceedings{06e3880559274e8f85c1ea435f0521fb,
title = "Evolutionary negotiation in agent-mediated commerce",
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{\textquoteright}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{\textquoteright} utility. Our goal is to develop an automated negotiator that guides the negotiation process so as to maximize both parties{\textquoteright} payoff.",
author = "Choi, {Samuel P.M.} and Jiming Liu and Chan, {Sheung Ping}",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2001.; 6th International Computer Science Conference on Active Media Technology, AMT 2001 ; Conference date: 18-12-2001 Through 20-12-2001",
year = "2001",
doi = "10.1007/3-540-45336-9_27",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "224--234",
editor = "Jiming Liu and Yuen, {Pong C.} and Chun-hung Li and Joseph Ng and Toru Ishida",
booktitle = "Active Media Technology - 6th International Computer Science Conference, AMT 2001, Proceedings",
}