Learning opponent´s eagerness with Bayesian updating rule in a market-driven negotiation model

Sim proposed a market-driven negotiation model [I] for designing negotiation agents. Although agent itself eagerness was taken into consideration as a fixed value in Sim´s proposed model, opponent´s eagerness was not considered. This paper proposes an improved market-driven negotiation model in which Bayesian updating rule is applied to learn opponent´s eagerness since opponent´s eagerness is unknown to an agent and may vary with dynamic changing market situation.