Improving trade-offs in automated bilateral negotiations for expressive and inexpressive scenarios

Abstract

In multi-issue bilateral negotiations, it is possible to make issue trade-offs to allow agents to search for win-win solutions. Different techniques may be used to perform these trade-offs. In particular, similarity criteria have been successfully used in this context. However, one drawback of similarity-based trade-offs is that this approach behaves differently depending on the knowledge each agent has about its counterpart, and depending on the order in which the different issues are considered. To address this problem, in this paper we propose three new mechanisms to improve the search for joint gains. Two of them are applicable in expressive scenarios, where agents may be willing to share preference information, while the third one is intended for inexpressive scenarios. The experimental evaluation shows how our proposals improve the efficiency and optimality of the negotiation process over previous approaches.