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AI Agents Break Rules Under Everyday Pressure

RL is more information inefficient than you thought

CS234: Reinforcement Learning Winter 2025

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Jasmine: A Simple, Performant and Scalable Jax-Based World Modeling Codebase

Show HN: Cancer diagnosis makes for an interesting RL environment for LLMs

Cursor Composer: Building a fast frontier model with RL

Agent Lightning: Train agents with RL (no code changes needed)

OpenAI at QCon AI NYC: Fine Tuning the Enterprise

At QCon AI NYC 2025, Will Hang from OpenAI unveiled Agent RFT—a cutting-edge reinforcement fine-tuning approach for tool-using agents. By optimizing prompts and tasks before model adjustments, Hang showcased effective strategies to enhance decision-making and efficiency, emphasizing a balanced grading system. The session revealed a future where smarter agents reduce latency and improve outcomes. By Andrew Hoblitzell

The performance of Minimax-m2 is truly impressive!

A new autonomous fighter jet just broke cover. It's powered by the same AI brain that flew an F-16 through a dogfight.

[P] CleanMARL : a clean implementations of Multi-Agent Reinforcement Learning Algorithms in PyTorch

[R] No Prompt Left Behind: Exploiting Zero-Variance Prompts in LLM Reinforcement Learning via Entropy-Guided Advantage Shaping

Richard Sutton – Father of RL thinks LLMs are a dead end

Gpt-oss Reinforcement Learning - Fastest inference now in Unsloth! (<15GB VRAM)

[P] SDLArch-RL: Multi-Console Gaming Environment for Reinforcement Learning Research

[R] MiniGrid DoorKeys Benchmark Active Inference

[R] r-rpe: beyond openai’s rl-hf — hedging ↓60% in eval-only tests

RL ReSearch

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DR-Tulu-8B

Xiaomi MiMo

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MiMo-7B-RL

DLR-RM

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stable-baselines3

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

vwxyzjn

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cleanrl

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

facebookresearch

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habitat-lab

A modular high-level library to train embodied AI agents across a variety of tasks and environments.

microsoft

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qlib

Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.

google-deepmind

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mujoco

Multi-Joint dynamics with Contact. A general purpose physics simulator.

Farama-Foundation

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Gymnasium

An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)