562 Open source projects that are alternatives of or similar to omd

MuZero

Bayesian Optimization in JAX

Wolpertinger Training with DDPG (Pytorch), Deep Reinforcement Learning in Large Discrete Action Spaces. Multi-GPU/Singer-GPU/CPU compatible.

"Continuous Deep Q-Learning with Model-based Acceleration" in TensorFlow

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DeepRL algorithms implementation easy for understanding and reading with Pytorch and Tensorflow 2(DQN, REINFORCE, VPG, A2C, TRPO, PPO, DDPG, TD3, SAC)

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2022/Spring 2022

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

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Structural implementation of RL key algorithms

AI research environment for the Atari 2600 games 🤖.

Deep recurrent Q Learning using Tensorflow, openai/gym and openai/retro

PyTorch implementation of Soft Actor-Critic (SAC)

PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)

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ADAM implements a collection of algorithms for calculating rigid-body dynamics in Jax, CasADi, PyTorch, and Numpy.

Revisiting Rainbow

Deep Reinforcement Learning (DQN) based Self Driving Car Control with Vehicle Simulator

No description or website provided.

DrQ: Data regularized Q

TensorFlow implementation of Deep Reinforcement Learning papers

PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.

强化学习中文教程，在线阅读地址：https://datawhalechina.github.io/easy-rl/

Reinforcement learning with tensorflow 2 keras

No description or website provided.

Mxnet implementation of Deep Reinforcement Learning papers, such as DQN, PG, DDPG, PPO

Deep Recurrent Q-Learning vs Deep Q Learning on a simple Partially Observable Markov Decision Process with Minecraft

🤖 Implements of Reinforcement Learning algorithms.

31 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.

A simple example of how to implement vector based DQN using PyTorch and a ML-Agents environment

A operator overloading, tape-based, reverse-mode AD

Source Code Generation for Automatic Differentiation using Operator Overloading

DSL for forward and reverse mode automatic differentiation in Haskell. Port of DiffSharp.

A common interface for quadrature and numerical integration for the SciML scientific machine learning organization

(AAAI 2018) Action Branching Architectures for Deep Reinforcement Learning

One More Einsum for Julia! With runtime order-specification and high-level adjoints for AD

Differentiable Programming Tensor Networks

Algorithms that combine tensor network methods with automatic differentiation

Numerically solves equations of motion for a given Hamiltonian function

A probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods.

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QuantumFlow: A Quantum Algorithms Development Toolkit

A .NET library that provides fast, accurate and automatic differentiation (computes derivative / gradient) of mathematical functions.

Automatic Differentiation for Tensor Algebras

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Automatic Differentiation using Pseudo Lenses. Neat.

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C++ template library for probabilistic programming

Elastic Full Waveform Inversion for Subsurface Flow Problems Using Intrusive Automatic Differentiation

Abstract operators for large scale optimization in Julia

Differentiable interface to FEniCS for JAX using dolfin-adjoint/pyadjoint