Design of Negotiation Agents Based on Behavior Models

Despite the widespread adoption of e-commerce and online purchasing by consumers over the last two decades, automated software agents that can negotiate the issues of an e-commerce transaction with consumers still do not exist. A major challenge in designing automated agents lies in the ability to predict the consumer’s behavior adequately throughout the negotiation process. We employ switching linear dynamical systems (SLDS) within a minimum description length framework to predict the consumer’s behavior. Based on the SLDS prediction model, we design software agents that negotiate e-commerce transactions with consumers on behalf of online merchants. We evaluate the agents through simulations of typical negotiation behavior models discussed in the negotiation literature and actual buyer behavior from an agent-human negotiation experiment.