Alternate Strategies for a Win-Win Seeking Agent in Agent-Human Negotiations

A Study of Integrative Bargaining Model with Argumentation-Based Negotiation

E-commerce is increasingly competitive and there is a constant need for new approaches and technology to facilitate exchange. Emerging techniques include the use of artificial intelligence (AI). One AI tool that has sparked interest in e-commerce is the automated negotiation agent (negotiation-agent). This study examines such agents, and proposes an offer strategy model of integrative negotiation for a negotiation-agent with a focus on negotiation agent-to-human interaction. More specifically, a new offer strategy was developed based on the integrative bargaining model, which emphasizes the importance of exchanging information among negotiators and multi-issue negotiation that includes package offers to achieve an integrative (win-win) outcome. This study incorporated an argumentation-based negotiation and the negotiation tactic of multiple equivalent simultaneous offers, which was programmed into the negotiation-agent. An experiment was conducted performing 49 negotiation-agent-to-human negotiations over three issues in online purchase tasks to demonstrate the effectiveness of the proposed strategy. Experimental results indicated that the proposed offer strategy with agent negotiation can enhance the persuasiveness of an offer and the performance of negotiation outcome (human counterpart’s perception toward negotiation process, opponent–agent and desire for future negotiation). The findings confirmed the effectiveness of the proposed design and demonstrated an innovative approach to e-commerce transactions.