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Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research

arXiv 1903.00742 ↗First posted 2 Mar 2019cs.AI cs.GT cs.MAcited by 58

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Abstract (arXiv)

Evolution has produced a multi-scale mosaic of interacting adaptive units. Innovations arise when perturbations push parts of the system away from stable equilibria into new regimes where previously well-adapted solutions no longer work. Here we explore the hypothesis that multi-agent systems sometimes display intrinsic dynamics arising from competition and cooperation that provide a naturally emergent curriculum, which we term an autocurriculum. The solution of one social task often begets new social tasks, continually generating novel challenges, and thereby promoting innovation. Under certain conditions these challenges may become increasingly complex over time, demanding that agents accumulate ever more innovations.

Key facts. Cited by 58 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Mar 2019.

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Citing papers per year: 2021: 14; 2022: 10; 2023: 13; 2024: 8; 2025: 8; 2026: 5.

58 papers.

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  1. 2021Open-Ended Learning Leads to Generally Capable Agentscited by 177
  2. 2023Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordiacited by 119
  3. 2021Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Potcited by 97
  4. 2021From Motor Control to Team Play in Simulated Humanoid Footballcited by 87
  5. 2024Open-Endedness is Essential for Artificial Superhuman Intelligencecited by 79
  6. 2021Modelling Behavioural Diversity for Learning in Open-Ended Gamescited by 39
  7. 2022Environment Generation for Zero-Shot Compositional Reinforcement Learningcited by 32
  8. 2023MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learningcited by 30
  9. 2023A Review of Cooperation in Multi-agent Learningcited by 27
  10. 2021Variational Automatic Curriculum Learning for Sparse-Reward Cooperative Multi-Agent Problemscited by 25
  11. 2021Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systemscited by 24
  12. 2024A social path to human-like artificial intelligencecited by 20
38 more
  1. 2022Emergent Bartering Behaviour in Multi-Agent Reinforcement Learningcited by 18
  2. 2025Virtual Agent Economiescited by 17
  3. 2022It Takes Four to Tango: Multiagent Selfplay for Automatic Curriculum Generationcited by 14
  4. 2021Adversarial Environment Generation for Learning to Navigate the Webcited by 13
  5. 2021HAMMER: Multi-Level Coordination of Reinforcement Learning Agents via Learned Messagingcited by 12
  6. 2024Boundless Socratic Learning with Language Gamescited by 12
  7. 2021Learning in Matrix Games can be Arbitrarily Complexcited by 11
  8. 2022Social Network Structure Shapes Innovation: Experience-sharing in RL with SAPIENScited by 10
  9. 2022Learning Robust Real-Time Cultural Transmission without Human Datacited by 9
  10. 2023minimax: Efficient Baselines for Autocurricula in JAXcited by 9
  11. 2021Explore and Control with Adversarial Surprisecited by 6
  12. 2023Conceptual Framework for Autonomous Cognitive Entitiescited by 6
  13. 2024JaxLife: An Open-Ended Agentic Simulatorcited by 6
  14. 2026Generative AI collective behavior needs an interactionist paradigmcited by 6
  15. 2021Meta-control of social learning strategiescited by 5
  16. 2023Investigating the Impact of Direct Punishment on the Emergence of Cooperation in Multi-Agent Reinforcement Learning Systemscited by 5
  17. 2023An Invitation to Deep Reinforcement Learningcited by 5
  18. 2022Creative Problem Solving in Artificially Intelligent Agents: A Survey and Frameworkcited by 4
  19. 2023Towards Skilled Population Curriculum for Multi-Agent Reinforcement Learningcited by 4
  20. 2025Improving Environment Novelty Quantification for Effective Unsupervised Environment Designcited by 4
  21. 2025Deep RL Needs Deep Behavior Analysis: Exploring Implicit Planning by Model-Free Agents in Open-Ended Environmentscited by 4
  22. 2026Social physics in the age of artificial intelligencecited by 4
  23. 2026Human-like autonomy emerges from self-play and a pinch of human datacited by 4
  24. 2022Reward-Sharing Relational Networks in Multi-Agent Reinforcement Learning as a Framework for Emergent Behaviorcited by 3
  25. 2022Game Theoretic Rating in N-player general-sum games with Equilibriacited by 3
  26. 2023Emergent collective intelligence from massive-agent cooperation and competitioncited by 3
  27. 2021Neural Auto-Curriculacited by 2
  28. 2022Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environmentscited by 2
  29. 2023Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decompositioncited by 2
  30. 2023Learning Curricula in Open-Ended Worldscited by 2
  31. 2024Syllabus: Portable Curricula for Reinforcement Learning Agentscited by 2
  32. 2024Incentives to Build Houses, Trade Houses, or Trade House Building Skills in Simulated Worlds under Various Governing Systems or Institutions: Comparing Multi-agent Reinforcement Learning to Generative Agent-based Modelcited by 2
  33. 2025TAG: A Decentralized Framework for Multi-Agent Hierarchical Reinforcement Learningcited by 2
  34. 2025Beyond Fixed Tasks: Unsupervised Environment Design for Task-Level Pairscited by 2
  35. 2026FinEvo: From Isolated Backtests to Ecological Market Games for Multi-Agent Financial Strategy Evolutioncited by 2
  36. 2023Differentiable Arbitrating in Zero-sum Markov Gamescited by 1
  37. 2024Dynamics of Moral Behavior in Heterogeneous Populations of Learning Agentscited by 1
  38. 2025The Emergence of Complex Behavior in Large-Scale Ecological Environmentscited by 1

50 most cited of 58 All 58 (JSON)