Accepting Optimally with Incomplete Information

Abstract

In the previous chapter we classified generic acceptance conditions, and we formulated new ones that performed better in an experimental setting. This chapter takes a different approach by devising theoretically optimal solutions. We approach the decision of whether to accept as a sequential decision problem, by modeling the bids received as a stochastic process. We argue that this is a natural choice in the context of a negotiationwith incomplete information, where the future behavior of the opponent is uncertain. We determine the optimal acceptance policies for particular opponent classes and we present an approach to estimate the expected range of offers when the type of opponent is unknown. We apply our method against a wide range of opponents, and compare its performance with acceptance mechanisms of stateof- the-art negotiation strategies. The experiments show that the proposed approach is able to find the optimal time to accept, and improves upon widely used existing acceptance mechanisms.