This work was presented at HAIDM 2014. The 2014 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: To date, a variety of automated negotiation agents have been created. While each of these agents has been shown to be effective in negotiating with people in specific environments, they lack natural language processing support required to enable real-world types of interactions. In this paper we present NegoChat, the first negotiation agent that successfully addresses this limitation. NegoChat contains several significant research contributions. First, we found that simply modifying existing agents to include an NLP module is insufficient to create these agents. Instead, the agents’ strategies must be modified to address partial agreements and issue-by-issue interactions. Second, we present NegoChat’s negotiation algorithm. This algorithm is based on bounded rationality, and specifically Aspiration Adaptation Theory (AAT). As per AAT, issues are addressed based on people’s typical urgency, or order of importance. If an agreement cannot be reached based on the value the human partner demands, the agent retreats, or downwardly lowers the value of previously agreed upon issues so that a “good enough” agreement can be reached on all issues. This incremental approach is fundamentally different from all other negotiation agents, including the state-of-the-art KBAgent. Finally, we present a rigorous evaluation of NegoChat, showing its effectiveness.

Keywords: Human-Agent Systems, Negotiation, Chat Agent.

Citation: Avi Rosenfeld. NegoChat: A Chat-Based Negotiation Agent.

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This work was presented at HAIDM 2014. The 2014 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: This paper studies commitment strategies in three-player negotiation settings comprising human players and computer agents. We defined a new game called the Contract Game which is analogous to real-world market settings in which participants need to reach agreement over contracts in order to succeed. The game comprises three players, two service providers and one customer. The service providers compete to make repeated contract offers to the customer consisting of resource exchanges in the game. We formally analyzed the game and defined sub-game perfect equilibrium strategies for the customer and service providers that involve commitments. We conducted extensive empirical studies of these strategies in three different countries, the U.S., Israel and China. We ran several configurations in which two human participants played a single agent using the equilibrium strategies in various role configurations in the game (both customer and service providers). Our results showed that the computer agent using equilibrium strategies for the customer role was able to outperform people playing the same role in all three countries. In contrast, the computer agent playing the role of the service provider was not able to outperform people. Analysis reveals this difference in performance is due to the contracts proposed in equilibrium being significantly beneficial to the customer players, as well as irrational behavior taken by human customer players in the game.

Citation: Galit Haim, Kobi Gal, Bo An and Sarit Kraus. Equilibrium Strategies for Human-Computer Negotiation in 3-player market settings.

Download: http://bit.ly/1QfXcFa