mlsanityData to 7 Oct 2026

Cooperative-Competitive Team Play of Real-World Craft Robots

arXiv 2602.21119 ↗First posted 24 Feb 2026cs.RO cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

Multi-agent deep Reinforcement Learning (RL) has made significant progress in developing intelligent game-playing agents in recent years. However, the efficient training of collective robots using multi-agent RL and the transfer of learned policies to real-world applications remain open research questions. In this work, we first develop a comprehensive robotic system, including simulation, distributed learning framework, and physical robot components. We then propose and evaluate reinforcement learning techniques designed for efficient training of cooperative and competitive policies on this platform. To address the challenges of multi-agent sim-to-real transfer, we introduce Out of Distribution State Initialization (OODSI) to mitigate the impact of the sim-to-real gap. In the experiments, OODSI improves the Sim2Real performance by 20%. We demonstrate the effectiveness of our approach through experiments with a multi-robot car competitive game and a cooperative task in real-world settings.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 45 of its 65 references that are in the map. First posted on arXiv 24 Feb 2026.

Builds on

45 of 65 references.

References · 45

  1. 2017Proximal Policy Optimization Algorithmscited by 14,441
  2. 2022Do As I Can, Not As I Say: Grounding Language in Robotic Affordancescited by 2,302
  3. 2017Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environmentscited by 1,519
  4. 2017Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real Worldcited by 1,401
  5. 2019Dota 2 with Large Scale Deep Reinforcement Learningcited by 1,084
  6. 2021The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Gamescited by 903
  7. 2017Counterfactual Multi-Agent Policy Gradientscited by 733
  8. 2018Learning Dexterous In-Hand Manipulationcited by 643
  9. 2017Sim-to-Real Transfer of Robotic Control with Dynamics Randomizationcited by 616
  10. 2019The StarCraft Multi-Agent Challengecited by 589
  11. 2020Learning Quadrupedal Locomotion over Challenging Terraincited by 494
  12. 2019Learning agile and dynamic motor skills for legged robotscited by 402
33 more
  1. 2019Emergent Tool Use From Multi-Agent Autocurriculacited by 308
  2. 2022Learning robust perceptive locomotion for quadrupedal robots in the wildcited by 299
  3. 2017StarCraft II: A New Challenge for Reinforcement Learningcited by 268
  4. 2020Learning Agile Robotic Locomotion Skills by Imitating Animalscited by 229
  5. 2016CAD2RL: Real Single-Image Flight without a Single Real Imagecited by 227
  6. 2017Reverse Curriculum Generation for Reinforcement Learningcited by 185
  7. 2019Mastering Complex Control in MOBA Games with Deep Reinforcement Learningcited by 150
  8. 2022Rapid Locomotion via Reinforcement Learningcited by 130
  9. 2018Sim-to-Real Reinforcement Learning for Deformable Object Manipulationcited by 124
  10. 2023Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learningcited by 111
  11. 2023ANYmal Parkour: Learning Agile Navigation for Quadrupedal Robotscited by 105
  12. 2022Deep Whole-Body Control: Learning a Unified Policy for Manipulation and Locomotioncited by 98
  13. 2021From Motor Control to Team Play in Simulated Humanoid Footballcited by 87
  14. 2019BayesSim: adaptive domain randomization via probabilistic inference for robotics simulatorscited by 78
  15. 2024Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Controlcited by 63
  16. 2017Data-efficient Deep Reinforcement Learning for Dexterous Manipulationcited by 61
  17. 2022Adapting Rapid Motor Adaptation for Bipedal Robotscited by 39
  18. 2022GenLoco: Generalized Locomotion Controllers for Quadrupedal Robotscited by 36
  19. 2023Dynamic Handover: Throw and Catch with Bimanual Handscited by 33
  20. 2023Lifelike Agility and Play in Quadrupedal Robots using Reinforcement Learning and Generative Pre-trained Modelscited by 30
  21. 2017Beating Atari with Natural Language Guided Reinforcement Learningcited by 24
  22. 2022Learning Torque Control for Quadrupedal Locomotioncited by 22
  23. 2020TStarBot-X: An Open-Sourced and Comprehensive Study for Efficient League Training in StarCraft II Full Gamecited by 21
  24. 2022Transferring Multi-Agent Reinforcement Learning Policies for Autonomous Driving using Sim-to-Realcited by 16
  25. 2020TLeague: A Framework for Competitive Self-Play based Distributed Multi-Agent Reinforcement Learningcited by 11
  26. 2023Learning Agile Bipedal Motions on a Quadrupedal Robotcited by 10
  27. 2023Partially Observable Mean Field Multi-Agent Reinforcement Learning Based on Graph-Attentioncited by 7
  28. 2019Multi-Vehicle Mixed-Reality Reinforcement Learning for Autonomous Multi-Lane Drivingcited by 6
  29. 2022E-MAPP: Efficient Multi-Agent Reinforcement Learning with Parallel Program Guidancecited by 6
  30. 2023Multi-Agent Reinforcement Learning for Cooperative Air Transportation Services in City-Wide Autonomous Urban Air Mobilitycited by 6
  31. 2024Learning Highly Dynamic Behaviors for Quadrupedal Robotscited by 6
  32. 2023MARBLER: An Open Platform for Standardized Evaluation of Multi-Robot Reinforcement Learning Algorithmscited by 3
  33. 2020Cooperative Control of Mobile Robots with Stackelberg Learningcited by 2

Built on by

Not cited yet.