In this article, we consider the novel approach of a seller and customer negotiating bilaterally about a two-part tariff, using autonomous software agents. An advantage of this approach is that win-win opportunities can be generated while keeping the problem of preference elicitation as simple as possible. We develop bargaining strategies that software agents can use to conduct the actual bilateral negotiation on behalf of their owners. We present a decomposition of bargaining strategies into concession strategies and Pareto-efficient-search methods: Concession and Paretosearch strategies focus on the conceding and win-win aspect of bargaining, respectively. An important technical contribution of this article lies in the development of two Pareto-search methods. Computer experiments show, for various concession strategies, that the respective use of these two Pareto-search methods by the two negotiators results in very efficient bargaining outcomes while negotiators concede the amount specified by their concession strategy.
REF proposed a negotiation mechanism where the bargaining strategy is decomposed into a concession strategy and a Paretosearch strategy.
Efficient Methods for Automated Multi-Issue Negotiation: Negotiating over a Two-Part Tariff
Int. J. Intell. Syst.
Int. J. Intell. Syst.
Mathematics Computer Science