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The Learning of an Opponent's Approximate Preferences in Bilateral Automated Negotiation
Journal of Theoretical and Applied Electronic Commerce Research
Autonomous agents can negotiate on behalf of buyers and sellers to make a contract in the e-marketplace. In bilateral negotiation, they need to find a joint agreement by satisfying each other. That is, an agent should learn its opponent's preferences. However, the agent has limited time to find an agreement while trying to protect its payoffs by keeping its preferences private. In doing so, generating offers with incomplete information about the opponent's preferences is a complex process and,doi:10.4067/s0718-18762011000300006 fatcat:2rvsw5nkpbfbzovceswjshn3yu