mlsanityData to 14 Oct 2026

Emergent Communication through Negotiation

arXiv 1804.03980 ↗First posted 11 Apr 2018cs.AI cs.CL cs.LGcited by 62

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Abstract (arXiv)

Multi-agent reinforcement learning offers a way to study how communication could emerge in communities of agents needing to solve specific problems. In this paper, we study the emergence of communication in the negotiation environment, a semi-cooperative model of agent interaction. We introduce two communication protocols -- one grounded in the semantics of the game, and one which is textita priori ungrounded and is a form of cheap talk. We show that self-interested agents can use the pre-grounded communication channel to negotiate fairly, but are unable to effectively use the ungrounded channel. However, prosocial agents do learn to use cheap talk to find an optimal negotiating strategy, suggesting that cooperation is necessary for language to emerge. We also study communication behaviour in a setting where one agent interacts with agents in a community with different levels of prosociality and show how agent identifiability can aid negotiation.

Key facts. Cited by 62 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Apr 2018.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 17; 2022: 13; 2023: 9; 2024: 9; 2025: 8; 2026: 6.

62 papers.

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  1. 2022A Survey of Multi-Agent Deep Reinforcement Learning with Communicationcited by 104
  2. 2024How Well Can LLMs Negotiate? NegotiationArena Platform and Analysiscited by 100
  3. 2021CaSiNo: A Corpus of Campsite Negotiation Dialogues for Automatic Negotiation Systemscited by 62
  4. 2025Embodied AI Agents: Modeling the Worldcited by 61
  5. 2021Deep Multiagent Reinforcement Learning: Challenges and Directionscited by 42
  6. 2021Learning to Ground Multi-Agent Communication with Autoencoderscited by 37
  7. 2025The Traitors: Deception and Trust in Multi-Agent Language Model Simulationscited by 34
  8. 2021Few-shot Language Coordination by Modeling Theory of Mindcited by 32
  9. 2021On the Critical Role of Conventions in Adaptive Human-AI Collaborationcited by 27
  10. 2022Scalable Multi-Agent Model-Based Reinforcement Learningcited by 25
  11. 2021Learning to Draw: Emergent Communication through Sketchingcited by 23
  12. 2022AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-Ncited by 22
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  1. 2024K-Level Reasoning: Establishing Higher Order Beliefs in Large Language Models for Strategic Reasoningcited by 21
  2. 2021Quasi-Equivalence Discovery for Zero-Shot Emergent Communicationcited by 19
  3. 2021Emergent Communication under Competitioncited by 18
  4. 2024Designing for Human-Agent Alignment: Understanding what humans want from their agentscited by 18
  5. 2024A Review of the Applications of Deep Learning-Based Emergent Communicationcited by 17
  6. 2021Emergent Graphical Conventions in a Visual Communication Gamecited by 16
  7. 2022Distributed Reinforcement Learning for Robot Teams: A Reviewcited by 16
  8. 2022Adversarial Cheap Talkcited by 16
  9. 2023Computational Language Acquisition with Theory of Mindcited by 15
  10. 2021The Emergence of the Shape Bias Results from Communicative Efficiencycited by 13
  11. 2023Towards More Human-like AI Communication: A Review of Emergent Communication Researchcited by 13
  12. 2025Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordiacited by 12
  13. 2026The Five Ws of Multi-Agent Communication: Who Talks to Whom, When, What, and Why -- A Survey from MARL to Emergent Language and LLMscited by 10
  14. 2023Information Design in Multi-Agent Reinforcement Learningcited by 9
  15. 2025Teacher Demonstrations in a BabyLM's Zone of Proximal Development for Contingent Multi-Turn Interactioncited by 9
  16. 2022RILI: Robustly Influencing Latent Intentcited by 8
  17. 2021Normative Disagreement as a Challenge for Cooperative AIcited by 7
  18. 2024Advantage Alignment Algorithmscited by 7
  19. 2021Visual Perspective Taking for Opponent Behavior Modelingcited by 6
  20. 2022MA-Dreamer: Coordination and communication through shared imaginationcited by 6
  21. 2023Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learningcited by 6
  22. 2021The emergence of visual semantics through communication gamescited by 5
  23. 2022Learning Latent Representations to Co-Adapt to Humanscited by 5
  24. 2024Enhancing Language Model Rationality with Bi-Directional Deliberation Reasoningcited by 5
  25. 2022Over-communicate no more: Situated RL agents learn concise communication protocolscited by 4
  26. 2021TexRel: a Green Family of Datasets for Emergent Communications on Relationscited by 3
  27. 2021Targeted Data Acquisition for Evolving Negotiation Agentscited by 3
  28. 2021Learning to Guide and to Be Guided in the Architect-Builder Problemcited by 3
  29. 2022Emergence of Machine Language: Towards Symbolic Intelligence with Neural Networkscited by 3
  30. 2022Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysiscited by 3
  31. 2023Emergent Communication in Interactive Sketch Question Answeringcited by 3
  32. 2022Recommendations for Systematic Research on Emergent Languagecited by 2
  33. 2024A Contextual Combinatorial Bandit Approach to Negotiationcited by 2
  34. 2025Playpen: An Environment for Exploring Learning Through Conversational Interactioncited by 2
  35. 2025Learning Robust Social Strategies with Large Language Modelscited by 2
  36. 2026Investigating the Development of Task-Oriented Communication in Vision-Language Modelscited by 2
  37. 2026Bandwidth-Efficient Multi-Agent Communication through Information Bottleneck and Vector Quantizationcited by 2
  38. 2021gComm: An environment for investigating generalization in Grounded Language Acquisitioncited by 1

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