Learning human negotiation behavior across cultures

The ability to negotiate successfully is critical in many social interactions. The dissemination of applications such as the Internet across geographical and ethnic borders are opening up opportunities for computer agents to negotiate with people of diverse cultural and organizational affiliation. These automated negotiators should be able to proficiently interact and collaborate with their human partners. In this paper we compare several techniques for modeling the negotiation behavior of people across three different countries. Culture plays an important role in people's decision making and people differ in the way make offers and fulfil their commitments in negotiation across cultures. We consider a setting that included multiple rounds of negotiation with non-binding agreements. Participants in each of the countries interacted with a computer agent that used a baseline negotiation strategy that adapted to the extent to which participants were helpful and reliable. The models considered various features of the negotiation task, such as the extent to which proposals are generous and helpful to participants and whether participants fulfil their agreements. Our models achieved high accuracy rates in predicting important decisions that are made in negotiation such as whether participants reach agreement and the extent to which they are reliable in different situations. We show that the features that best vary the prediction accuracy depend on people's cultural affiliation in addition to their actual negotiation behavior. These models for predicting human behavior in negotiation will form the basis of a computer agent that can successfully negotiate with people across cultures.