Reinforcement Learning
Showing 36 of 150 projects
An OpenAI Gym extension for robotics simulation using ROS and Gazebo to benchmark and develop robot behaviors.
A diverse suite of scalable reinforcement learning environments written in JAX for hardware-accelerated research.
A Bitcoin trading bot using deep reinforcement learning (TensorForce) to automate buy/sell/hold decisions based on price history.
A chess AI that learns to play chess using deep learning and neural networks.
A comprehensive Swift framework providing AI/ML algorithms including neural networks, SVMs, genetic algorithms, and MDPs with GPU acceleration.
A comprehensive Swift framework providing AI/ML algorithms including neural networks, SVMs, PCA, genetic algorithms, and MDPs with GPU acceleration support.
An OpenAI Gym environment for stock market trading simulation with Deep Q-learning and Policy Gradient implementations.
JAX (Flax) implementations of reinforcement learning algorithms for continuous action spaces, designed for research.
A lightweight Ruby playground with clean, readable implementations of core AI algorithms for learning and experimentation.
A lightweight Ruby playground with clean implementations of core AI algorithms for learning and experimentation.
A deep reinforcement learning framework for crowd-aware robot navigation using attention mechanisms to model human-robot and human-human interactions.
ROS package implementing a deep reinforcement learning algorithm for dynamic obstacle avoidance in ground robots.
A curated reading list of papers, datasets, and simulators for embodied vision research, covering navigation, interaction, and reasoning.
A curated collection of Monte Carlo tree search research papers with implementations from top AI conferences.
A reinforcement learning environment for training AI agents to manipulate malware samples and evade static machine learning detection.
An OpenAI Gym environment wrapper for the CARLA autonomous driving simulator, enabling reinforcement learning research.
A collection of GPU-accelerated parallel game simulators for reinforcement learning, built with JAX.
A large-scale StarCraft: Brood War replay dataset for AI research, containing 65,646 games with frame and action data.
A unified deep learning and reinforcement learning framework supporting multiple backends and hardware platforms.
A JavaScript library for reinforcement learning using Markov Decision Processes, implemented in C++ for performance.
A reinforcement learning framework for portfolio management that learns optimal trading strategies through online training.
A PyTorch reinforcement learning library implementing DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, and IMPALA.
A high-level machine learning library for Go with a Keras-like API, built on Gorgonia.
A reinforcement learning framework for de novo drug design that generates novel molecular structures with desired properties.
A hardware-accelerated Python library for running Quality-Diversity and neuroevolution algorithms in minutes instead of days.
An open-source toolkit for building end-to-end trainable task-oriented dialogue models with neural networks.
A simple, deterministic real-time strategy game environment designed for AI and reinforcement learning research.
A reinforcement learning library for Go providing agents, composable tooling, and visualization for solving environment challenges.
An application-oriented Deep Reinforcement Learning framework for real-world decision problems, covering simulation to deployment.
A reinforcement learning environment for training trading agents using real Korean equities orderbook and execution data.
Turn Godot projects into OpenAI Gym environments for training reinforcement learning models with PyTorch via shared memory.
An API conversion tool providing Gymnasium and PettingZoo bindings for popular external reinforcement learning environments.
A lightweight multilayer perceptron neural network library for MicroPython, designed for embedded systems like ESP32 and Pycom modules.
A Torch7 package providing extended neural network modules, criterions, and utilities for deep learning research.
A JAX-powered reimplementation of MiniGrid offering over 1000x speedup for reinforcement learning experiments.
A trading environment for reinforcement learning agents, supporting backtesting, live trading, and multiple RL algorithms.
Related Tags
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.