Iron Ore Negotiation

Iron ore negotiation research focuses on developing and evaluating computational models capable of autonomously negotiating resource allocation and pricing, mirroring real-world complexities. Current research employs various approaches, including contextual combinatorial bandits, gradient-based algorithms, and large language models (LLMs) with incorporated personality traits, to improve negotiation efficiency and fairness. These models are being tested and refined using diverse scenarios, from simple resource allocation games to complex multi-party, multi-issue negotiations, often incorporating human-in-the-loop evaluations. This work has implications for both advancing artificial intelligence and improving our understanding of human negotiation strategies, with potential applications in resource management, contract law, and conflict resolution.