Deal Me Maybe: The Role of Emotions in Multi-Agent Negotiation

arXiv:2608.06922 · cs.AI · Submitted 2026-08-07 · Read on arXiv

Massimiliano Luca, Apoorva Singh, Bruno Lepri

cs.AI

Submitted: 2026-08-07

Updated: 2026-08-10

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Deal Rate — 27× in this paper
• AI Agents — 3× in this paper · explained in 2 episodes
• Adam — 3× in this paper · explained in 3 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Evaluation Protocol — 2× in this paper · explained in 2 episodes
• Out-of-Budget Rate — 2× in this paper
• Agentic AI — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 4 episodes
• Calibration — 1× in this paper · explained in 9 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 8 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Human-in-the-loop — 1× in this paper · explained in 4 episodes
• Hyperparameters — 1× in this paper · explained in 2 episodes
• Language Models (LLMs) — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 9 episodes
• Out-of-Wholesale Rate — 1× in this paper
• Robustness — 1× in this paper · explained in 6 episodes

Sources

• Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• GPT-4o System Card

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