r/reinforcementlearning

Reinforcement learning research discussion.

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Latest from r/reinforcementlearning

  1. Breaking down how Anthropic actually achieved a 2x R&D speedup in just one yearhace 1 d
  2. [P] Pilot: self-play checkpoints that judge bot fights better judge human fights worse (ρ = −0.73), and my opponent-model "memory gain" turned out to be a baseline artifacthace 2 d
  3. Blogs kind of resources for RLhace 2 d
  4. PPO on Temple Run: pixels did worse than random, so I read the game's memory instead (lessons + 30-run eval)hace 2 d
  5. Multiple robots in one MuJoCo world vs. one robot per parallel environment.hace 2 d
  6. [Project] Aionterra: learning from different bodies in one continuous worldhace 3 d
  7. In long-horizon agentic RL, tokens/sec is the wrong metric. Your trainer is waiting on stragglershace 4 d
  8. "Could a modern chess engine on a Pentium have defeated Kasparov in 1996?", Nicholas Carlini 2026-11 (another chess time travel experiment)hace 4 d
  9. Thoughts on current state of RLlib?hace 4 d
  10. Rebuilt the "inside the RL agent's brain" visualization on corrected results two of its old claims didn't survivehace 4 d
  11. Corrected version of my "can an RL agent tell its world is fake" experiment: a GAE bootstrap bug barely moved the result, but follow-up controls changed what it meanshace 4 d
  12. SARSwarm: 4 AI drones (Multi-head) SAR mission (Metis-Core v0.4.2-Alpha)hace 5 d
  13. I trained a 4-drone autonomous combat swarm using continuous PPO in Unity 6 with sub-0.1ms Sentis inference (Zero NavMesh)hace 5 d
  14. [Research] Does LeWorldModel preserve local action geometry? Implications for model-based RL and planninghace 5 d
  15. Tried Claude + ElevenLabs to turn my article into a video - here's the summary at the end, full video link in the descriptionhace 5 d
  16. Fine-tuning a humanoid locomotion policy on scanned real-world sand: stock policy fell, fine-tuned held. How do you validate terrain physics in sim?hace 5 d
  17. Help me build a superhuman STS2 teacher (OstyAI)hace 6 d
  18. DeepSeek's "Exploring Super-Agent Design" explained in under 3 minutes! A fresh perspective on how agentic AI harnesses are designed and why they matter.hace 6 d
  19. Frame sampling can't prove something isn't in a videohace 6 d
  20. whichever the current rules list Same text, shortened, with focus on imitation learning data requirements.hace 6 d
  21. critique wanted: my agents' learning rate and discount come from their personality, plus a reward penalty i know is wronghace 6 d
  22. Exponential tilt view of RLVR: Stiemke duality decides when a pass@1 gain is free, and Karlin total positivity bounds the pass@k crossingshace 6 d
  23. League of Legends (Patch 26.19) - Ezreal AI 1v1hace 6 d
  24. Reward misspecification in documented cases (CoastRunners and others): how do you check that a high-return policy does what you intended?hace 6 d
  25. RL From Scratch: Introducing my NeatRL Library for Running RL algorithmshace 7 d

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