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• W2461497004 abstract "Artificial agents, coevolving under a machine learning regime, offer a promising basis for modeling adaptive behavior in multilateral negotiations and developing practical applications in electronic commerce. Results from simulations of bargaining in two coalition games demonstrate that simple artificial agents, adapting to one another under a genetic programming protocol (Koza, 1992), formulate effective strategies for negotiating agreements that both approximate those prescribed by the theory of cooperative games and rival the performance of humans negotiating in a laboratory situation." @default.
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• W2461497004 date "1996-07-28" @default.
• W2461497004 modified "2023-09-23" @default.
• W2461497004 title "Bargaining by artificial agents in two coalition games: a study in genetic programming for electronic commerce" @default.
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