Stars
Unified Implementations of Offline Reinforcement Learning Algorithms
Train transformer language models with reinforcement learning.
A generative world for general-purpose robotics & embodied AI learning.
Hardware-Accelerated Reinforcement Learning Algorithms in pure Jax!
Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.
Wasserstein Auto-encoded Markov Decision Processes: a framework to distill Reinforcement Learning policies into verifiable controllers with bisimulation guarantees
🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX
A C++ framework for MDPs and POMDPs with Python bindings
An extremely fast Python linter and code formatter, written in Rust.
A clean customizable documentation theme for Sphinx
🕹️ A diverse suite of scalable reinforcement learning environments in JAX
JAX and PZ RL envs + algorithms for swarms of CrazyFlies
Benchmarks for Multi-Objective Multi-Agent Decision Making
A new markup-based typesetting system that is powerful and easy to learn.
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
Multi-Objective Reinforcement Learning algorithms implementations.
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
You like pytorch? You like micrograd? You love tinygrad! ❤️
The Information Dynamics of Multidimensional Sequences
🎓 无需编写任何代码即可轻松创建漂亮的学术网站 Easily create a beautiful academic résumé or educational website using Hugo and GitHub. No code.
Multi-objective Gymnasium environments for reinforcement learning
JASP aims to be a complete statistical package for both Bayesian and Frequentist statistical methods, that is easy to use and familiar to users of SPSS