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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.

Toward Strategic Human Skill Development Through Human and Agent Interaction: Improving Negotiation Skill by Interacting with Bargaining Agent