Opponent's Preference Estimation Considering Their Offer Transition in Multi-Issue Closed Negotiations

Abstract

In recent years, agreement technologies have garnered interest among agents in the field of multi-agent systems. Automated negotiation is one of the agreement technologies, in which agents negotiate with each other to make an agreement so that they can solve conflicts between their preferences. Although most agents keep their own preferences private, it is necessary to estimate the opponent's preferences to obtain a better agreement. Therefore, opponent modeling is one of the most important elements in automated negotiating strategy. A frequency model is widely used for opponent modeling because of its robustness against various types of strategy while being easy to implement. However, existing frequency models do not consider the opponent's proposal speed and the transition of offers. This study proposes a novel frequency model that considers the opponent's behavior using two main elements: the offer ratio and the weighting function. The offer ratio stabilizes the model against changes in the opponent's offering speed, whereas the weighting function takes the opponent's concession into account. The two experiments conducted herein show that our proposed model is more accurate than other frequency models. Additionally, we find that the agent with the proposed model performs with a significantly higher utility value in negotiations.