Agent33: An Automated Negotiator with Heuristic Method for Searching Bids Around Nash Bargaining Solution

摘要

The international Automated Negotiating Agents Competition (ANAC) is being held annually since 2010 in order to bring together the researchers from the multi-agent negotiation community. In this regard, the Repeated Multilateral Negotiation League (RMNL), one of the four negotiation research challenges in ANAC 2018, requires participants to design and implement an intelligent negotiating agent, that is able to negotiate with two other opponents and that is able to learn from its previous negotiation experiences. In this context, in this paper, we design a negotiating agent that focuses on searching the space of suitable bids that provide high utilities for both sides near the Nash Bargaining Solution (NBS) using a novel heuristic method. The proposed agent has participated in the ANAC competition successfully and finished in the second place in the social welfare category.