Deal Me Maybe: The Role of Emotions in Multi-Agent Negotiation
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Abstract (arXiv)
Negotiation is a demanding social task for LLM agents, requiring strategic reasoning, persuasion, and interpersonal adaptation. Yet existing benchmarks often treat agents as emotionally neutral, overlooking a key driver of human bargaining behavior. We study how prompt-conditioned emotions affect LLM-based price negotiation. In a controlled framework, buyer and seller agents are independently assigned one of six emotional states and negotiate over 350 real consumer products under two budget conditions. Across 36 emotion-pair settings and five widely used LLMs, we find that emotions strongly shape outcomes. Angry buyers almost never reach agreement (0.39% deal rate), while happy buyers agree most often (28.91%), but obtain worse prices than fearful buyers. Emotion effects are role-dependent: buyer emotion mainly drives acceptance and rejection, whereas seller emotion shapes concession dynamics. These effects influence not only language, but also termination behavior and price trajectories, raising concerns for emotion-conditioned agents in commerce.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 21 references that are in the map. First posted on arXiv 7 Aug 2026.
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7 of 21 references.
References · 7
- 2025Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilitiescited by 3,796
- 2024TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Taskscited by 326
- 2024Proactive Agent: Shifting LLM Agents from Reactive Responses to Active Assistancecited by 87
- 2024Measuring Bargaining Abilities of LLMs: A Benchmark and A Buyer-Enhancement Methodcited by 48
- 2024Are LLMs Effective Negotiators? Systematic Evaluation of the Multifaceted Capabilities of LLMs in Negotiation Dialoguescited by 29
- 2024Assistive Large Language Model Agents for Socially-Aware Negotiation Dialoguescited by 18
- 2025Strategic Tradeoffs Between Humans and AI in Multi-Agent Bargainingcited by 11
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- 2024How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis
- 2025EvoEmo: Towards Evolved Emotional Policies for Adversarial LLM Agents in Multi-Turn Price Negotiation
- 2025Evaluating Multi-Turn Bargain Skills in LLM-Based Seller Agent
- 2026Can Induced Emotion Bias LLM Behaviors in Sequential Decision Making?
- 2026EmoDistill: Offline Emotion Skill Distillation for Language Model Agents in Adversarial Negotiation
- 2025How Does Cognitive Bias Affect Large Language Models? A Case Study on the Anchoring Effect in Price Negotiation Simulations
- 2026MERIT Feedback Elicits Better Bargaining in LLM Negotiators