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Show HN: ART – a new open-source RL framework for training agents

Mission Impossible: Managing AI Agents in the Real World

Watching 03 Model Sweat over a Paul Morphy Mate-in-2

Does RL Incentivize Reasoning in LLMs Beyond the Base Model?

Inner Loop Agents

Vending-Bench: A Benchmark for Long-Term Coherence of Autonomous Agents

Principles for Building One-Shot AI Agents

In Two Moves, AlphaGo and Lee Sedol Redefined the Future (2016)

Agency vs. Control vs. Reliability in Agent Design

A Practical Guide to Building Agents

This new paper poses a real threat to scaling RL

[P] The State of Reinforcement Learning for LLM Reasoning

[P] Training an LLM to play the board game Hex, using self-play to improve performance

The Simplest Mental Model for AI Agents Inspired by Autonomous Driving

INTELLECT-2: The First Globally Distributed Reinforcement Learning Training of a 32B Parameter Model

Google DeepMind's new AI used RL to discover its own RL algorithms: "It went meta and learned how to build its own RL system. And, incredibly, it outperformed all the RL algorithms we'd come up with ourselves over many years."

This is what an Agent is.

Tools for building deterministic AI agents with tool use and ranking logic

Xiaomi MiMo

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MiMo-7B-RL

google-deepmind

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mujoco

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

microsoft

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qlib

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.

DLR-RM

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stable-baselines3

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