r/reinforcementlearning

Reinforcement learning research discussion.

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r/reinforcementlearning 最新

  1. Breaking down how Anthropic actually achieved a 2x R&D speedup in just one year1 天前
  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 artifact2 天前
  3. Blogs kind of resources for RL2 天前
  4. PPO on Temple Run: pixels did worse than random, so I read the game's memory instead (lessons + 30-run eval)2 天前
  5. Multiple robots in one MuJoCo world vs. one robot per parallel environment.2 天前
  6. [Project] Aionterra: learning from different bodies in one continuous world3 天前
  7. In long-horizon agentic RL, tokens/sec is the wrong metric. Your trainer is waiting on stragglers4 天前
  8. "Could a modern chess engine on a Pentium have defeated Kasparov in 1996?", Nicholas Carlini 2026-11 (another chess time travel experiment)4 天前
  9. Thoughts on current state of RLlib?4 天前
  10. Rebuilt the "inside the RL agent's brain" visualization on corrected results two of its old claims didn't survive4 天前
  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 means4 天前
  12. SARSwarm: 4 AI drones (Multi-head) SAR mission (Metis-Core v0.4.2-Alpha)5 天前
  13. I trained a 4-drone autonomous combat swarm using continuous PPO in Unity 6 with sub-0.1ms Sentis inference (Zero NavMesh)5 天前
  14. [Research] Does LeWorldModel preserve local action geometry? Implications for model-based RL and planning5 天前
  15. Tried Claude + ElevenLabs to turn my article into a video - here's the summary at the end, full video link in the description5 天前
  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?5 天前
  17. Help me build a superhuman STS2 teacher (OstyAI)6 天前
  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.6 天前
  19. Frame sampling can't prove something isn't in a video6 天前
  20. whichever the current rules list Same text, shortened, with focus on imitation learning data requirements.6 天前
  21. critique wanted: my agents' learning rate and discount come from their personality, plus a reward penalty i know is wrong6 天前
  22. Exponential tilt view of RLVR: Stiemke duality decides when a pass@1 gain is free, and Karlin total positivity bounds the pass@k crossings6 天前
  23. League of Legends (Patch 26.19) - Ezreal AI 1v16 天前
  24. Reward misspecification in documented cases (CoastRunners and others): how do you check that a high-return policy does what you intended?6 天前
  25. RL From Scratch: Introducing my NeatRL Library for Running RL algorithms7 天前

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