Showing 61-80 of 104 projects
This TensorFlow code implements a curiosity-driven exploration algorithm for deep reinforcement learning.
A reinforcement learning-based approach to scale training of variational autoencoders (VLAs) used in AI tools.
A JavaScript library for building reinforcement learning agents, covering various RL algorithms.
A Python library for reinforcement learning, providing a simple and efficient way to implement RL algorithms.
A comprehensive implementation of all reinforcement learning algorithms in a simpler way.
TextWorld is a sandbox learning environment for training and evaluating reinforcement learning agents on text-based games.
An open-source package that allows game creators, AI researchers and hobbyists to build complex behaviors for non-player characters or agents.
A scalable toolkit for efficient model reinforcement learning in Python.
This repository provides valuable resources for researchers working on RL-based Reasoning MLLMs.
ReCall is a library for training large language models (LLMs) to reason and use tools via reinforcement learning.
PyTorch implementation of state-of-the-art reinforcement learning algorithms for vibe coders.
Comprehensive repository showcasing the latest advances in System-2 reasoning and LLM-based AI models.
A collection of high-quality, single-file implementations of state-of-the-art offline and offline-to-online reinforcement learning algorithms.
This GitHub repository is a curated list of reinforcement learning environments, which can be useful for AI and ML researchers and developers.
A repository for reinforcement learning (RL) implementations using PyTorch.
A curated list of awesome resources for model-based reinforcement learning.
Tools for training and deploying reinforcement learning models on the Unitree Go1 robot in a sim-to-real setting.
IDE for coordinating multi-agent AI swarms with support for various LLMs like Kimi-2.5 and GLM-4.7
A high-performance parallel environment execution engine for reinforcement learning environments.
PyTorch implementation of Deep Reinforcement Learning algorithms like TRPO, PPO, A2C, and GAIL.
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