Agent Negotiation

Agent negotiation research focuses on designing algorithms and models enabling autonomous agents to reach mutually beneficial agreements. Current efforts concentrate on developing efficient negotiation strategies using reinforcement learning, graph neural networks, and large language models (LLMs), often incorporating elements like reservation values and consideration of social welfare alongside individual utility. This field is significant for advancing artificial intelligence in complex interactive settings, with applications ranging from resource allocation in cloud computing to resolving disputes in online marketplaces and even facilitating international climate negotiations.