Enhancing Negotiation Outcomes by Understanding Human Arguments: A New Automated Agent Approach

What is it about?

This paper presents a novel automated agent designed to understand and utilize human arguments during negotiations. The agent analyzes natural language inputs from human negotiators to extract key information, such as preferences, constraints, and concessions. By classifying and incorporating these arguments into its negotiation strategy, the agent can adjust its offers more effectively. The system combines a hierarchical classification of argument types and an advanced opponent modeling technique to ensure the agent outperforms state-of-the-art methods. This makes it possible for the agent to generate well-targeted offers and reach better outcomes when negotiating with humans.

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Photo by Andy Kelly on Unsplash

Photo by Andy Kelly on Unsplash

Why is it important?

This work is important because it introduces a more sophisticated method for autonomous agents to handle negotiations with humans. By incorporating argument-based opponent modeling, the agent can better understand the preferences and constraints of human negotiators. This makes the negotiation process more human-centric and adaptive, leading to better outcomes for both parties. The timing of this research is critical as automated negotiation agents are increasingly being used in real-world applications, from business deal-making to resource allocation. The study also establishes a benchmark for future research in argument-based negotiation, making it a timely contribution to the field.

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