A bargaining agents model's it's opponent with entropy-based inference

Abstract

A negotiating agent engages in multi-issue bilateral negotiation in a dynamic information-rich environment. The agent aims to make informed decisions. The agent uses maximum entropy inference and minimum relative entropy inference to construct complete distributions in its world model from sparse observation data. The agent makes no assumptions about the internals of its opponent - it focuses only on the signals that it receives.