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Toward Strategic Human Skill Development Through Human and Agent Interaction: Improving Negotiation Skill by Interacting with Bargaining Agent
Author(s) -
Atsushi Otaki,
Kiyohiko Hattori,
Keiki Takadama
Publication year - 2010
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2010.p0831
Subject(s) - negotiation , computer science , profit (economics) , profit maximization , strategic interaction , knowledge management , microeconomics , human–computer interaction , economics , political science , law
This paper focuses on developing human skills through interaction between a human player and a computer agent, and explores its strategic method through experiments on the bargaining games where human players negotiate with computer agents. Specifically, human players negotiate with three types of agents: (a) strong/weak attitude agents making aggressive/defensive proposals in advantageous/disadvantageous situations; (b) fair agents making fair proposals; and (c) the “human-like” agents making mutually agreeable proposals as the number of games increases. Analysis of the human subject experiments has revealed the three major implications: (1) human players negotiating with the strong/weak attitude agents obtain the largest profit overall; (2) human players negotiating with “human-like” agents win many games; and (3) no relationship exists between profit maximization and a win of the games.

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