gym-forestReinforcement learning environment for the classical synthesis of quantum programs.
rl-resourcesA curated collection of reinforcement learning resources
RL-based-Graph2Seq-for-NQGCode & data accompanying the ICLR 2020 paper "Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation"
eco-dqnImplementation of ECO-DQN as reported in "Exploratory Combinatorial Optimization with Reinforcement Learning".
Deep-Q-NetworksImplementation of Deep/Double Deep/Dueling Deep Q networks for playing Atari games using Keras and OpenAI gym
AdaptivePELEAdaptivePELE is a Python package aimed at enhancing the sampling of molecular simulations
MaRLEnEMachine- and Reinforcement Learning ExtensioN for (game) Engines
vizdoomgymOpenAI Gym wrapper for ViZDoom enviroments
deep-rl-quadcopterImplementation of Deep Deterministic Policy Gradients (DDPG) to teach a Quadcopter How to Fly!
gym-hybridCollection of OpenAI parametrized action-space environments.
Quadcopter multi(Complete). An open-architecture multi-agent quadcopter simulator. We implement a few modern techniques for improving the performance of aerial vehicles, including reinforcement learning and shifting planar inequalities for obstacle avoidance.
rl-medicalCommunicative Multiagent Deep Reinforcement Learning for Anatomical Landmark Detection using PyTorch.
ElegantRLScalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥
pysc2StarCraft II Learning Environment
MDPNUnified notation for Markov Decision Processes PO(MDP)s
td-regTD-Regularized Actor-Critic Methods
Q-SnakeA Q-learning web visualizer for Snake built with React
MalmoRLA framework for training Reinforcement Learning agents in Minecraft with Project Malmö
RainbowRainbow DQN implementation accompanying the paper "Fast and Data-Efficient Training of Rainbow" which reaches 205.7 median HNS after 10M frames. 🌈
RL-code-resourcesA collection of Reinforcement Learning GitHub code resources divided by frameworks and environments
ml-playgroundSimple and easy-to-understand ml algorithm implementations
HandyRLHandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
Reinforcement Learning CourseCurso de Aprendizaje por Refuerzo, de 0 a 100 con notebooks y slides muy sencillas para entenderlo todo perfectamente.
myGymmyGym is suitable for fast prototyping of neural networks in the area of robotic manipulation and navigation. Our toolbox is fully modular, so that you can train your network with different robots, in several environments and on various tasks. You can also create a curriculum of tasks with increasing complexity and test your network on them. We …
intro rlAn Introduction to Reinforcement Learning
gym-anmDesign Reinforcement Learning environments that model Active Network Management (ANM) tasks in electricity distribution networks.
learningWalkthrough notebooks for Deep Learning, Machine Learning, Reinforcement Learning, Spark, Statistics, Algorithms, Scala, Python
protoProto-RL: Reinforcement Learning with Prototypical Representations
AlphaNPIAdapting the AlphaZero algorithm to remove the need of execution traces to train NPI.
ExplorerExplorer is a PyTorch reinforcement learning framework for exploring new ideas.
UnderflowWith underflow, create trafic light clusters that interact together to regulate circulation
deepbotsA wrapper framework for Reinforcement Learning in Webots simulator using Python 3.
koraliHigh-performance framework for uncertainty quantification, optimization and reinforcement learning.
es pytorchHigh performance implementation of Deep neuroevolution in pytorch using mpi4py. Intended for use on HPC clusters
racing dreamerLatent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing