mlsanityData to 7 Oct 2026

Learning to cooperate: Emergent communication in multi-agent navigation

arXiv 2004.01097 ↗First posted 2 Apr 2020cs.LG cs.CL cs.MAcited by 18

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Abstract (arXiv)

Emergent communication in artificial agents has been studied to understand language evolution, as well as to develop artificial systems that learn to communicate with humans. We show that agents performing a cooperative navigation task in various gridworld environments learn an interpretable communication protocol that enables them to efficiently, and in many cases, optimally, solve the task. An analysis of the agents' policies reveals that emergent signals spatially cluster the state space, with signals referring to specific locations and spatial directions such as "left", "up", or "upper left room". Using populations of agents, we show that the emergent protocol has basic compositional structure, thus exhibiting a core property of natural language.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Apr 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 5; 2023: 4; 2024: 2; 2025: 2; 2026: 1.

18 papers.

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  1. 2022A Survey of Multi-Agent Deep Reinforcement Learning with Communicationcited by 103
  2. 2021Interpretation of Emergent Communication in Heterogeneous Collaborative Embodied Agentscited by 19
  3. 2024A Review of the Applications of Deep Learning-Based Emergent Communicationcited by 17
  4. 2024SocraSynth: Multi-LLM Reasoning with Conditional Statisticscited by 13
  5. 2021Expressivity of Emergent Language is a Trade-off between Contextual Complexity and Unpredictabilitycited by 11
  6. 2022MA-Dreamer: Coordination and communication through shared imaginationcited by 6
  7. 2022Over-communicate no more: Situated RL agents learn concise communication protocolscited by 4
  8. 2021Towards Learning to Speak and Hear Through Multi-Agent Communication over a Continuous Acoustic Channelcited by 3
  9. 2023Emergent Communication in Interactive Sketch Question Answeringcited by 3
  10. 2025LLM-Mediated Guidance of MARL Systemscited by 3
  11. 2023A framework for the emergence and analysis of language in social learning agentscited by 2
  12. 2023Joining the Conversation: Towards Language Acquisition for Ad Hoc Team Playcited by 2
6 more
  1. 2022Detecting danger in gridworlds using Gromov's Link Conditioncited by 1
  2. 2023Cooperative Multi-Agent Learning for Navigation via Structured State Abstractioncited by 1
  3. 2025From Grunts to Lexicons: Emergent Language from Cooperative Foragingcited by 1
  4. 2021Toward Collaborative Reinforcement Learning Agents that Communicate Through Text-Based Natural Languagecited by 0
  5. 2022A Cooperative Reinforcement Learning Environment for Detecting and Penalizing Betrayalcited by 0
  6. 2026Robust and Efficient Communication for Multi-Agent Learningcited by 0