342 Open source projects that are alternatives of or similar to Underflow

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

No description or website provided.

A high-performance Atari A3C agent in 180 lines of PyTorch

Python code, PDFs and resources for the series of posts on Reinforcement Learning which I published on my personal blog

PyTorch implementation of Hierarchical Actor Critic (HAC) for OpenAI gym environments

🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!

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

Explorer is a PyTorch reinforcement learning framework for exploring new ideas.

Deep Reinforcement Learning with pytorch & visdom

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

Reinforcement Learning Algorithms

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

This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are still in progress)

Deep Reinforcement Learning in Autonomous Driving: the A3C algorithm used to make a car learn to drive in TORCS; Python 3.5, Tensorflow, tensorboard, numpy, gym-torcs, ubuntu, latex

PyTorch implementation of Soft Actor-Critic (SAC)

An experimentation framework for Reinforcement Learning using OpenAI Gym, Tensorflow, and Keras.

PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".

A Universal Deep Reinforcement Learning Framework

Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..

Implementations of Reinforcement Learning Models in Tensorflow

A3C LSTM Atari with Pytorch plus A3G design

Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO

Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

Code for Hands On Intelligent Agents with OpenAI Gym book to get started and learn to build deep reinforcement learning agents using PyTorch

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

DrQ: Data regularized Q

Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math

Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games

Minimal and Clean Reinforcement Learning Examples

JAX implementations of core Deep RL algorithms

[DeepRL Workshop, NeurIPS-21] Recurrent Off-policy Baselines for Memory-based Continuous Control (RDPG, RTD3 and RSAC)

source code for 'Improving automatic source code summarization via deep reinforcement learning'

Moore Machine Networks (MMN): Learning Finite-State Representations of Recurrent Policy Networks

Decentralized Reinforcment Learning: Global Decision-Making via Local Economic Transactions (ICML 2020)

In this repo I will try to gather all of the projects related to data science with clean datasets and high accuracy models to solve real world problems.

This repository hosts a customized PPO based agent for Carla. The goal of this project is to make it easier to interact with and experiment in Carla with reinforcement learning based agents -- this, by wrapping Carla in a gym like environment that can handle custom reward functions, custom debug output, etc.

Simple (but often Strong) Baselines for POMDPs in PyTorch - ICML 2022

Flappy Frog hack using Deep Reinforcement Learning (Deep Q-learning). 暴力膜蛤不可取。

Live Trading. Please star.

End to end motion planner using Deep Deterministic Policy Gradient (DDPG) in gazebo

AutoPentest-DRL: Automated Penetration Testing Using Deep Reinforcement Learning

End to End Mobile Robot Navigation using DDPG (Continuous Control with Deep Reinforcement Learning) based on Tensorflow + Gazebo

A pytorch based Gomoku game model. Alpha Zero algorithm based reinforcement Learning and Monte Carlo Tree Search model.

Code for our AAMAS 2020 paper: "A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry".

pytorch implementation of Curiosity-driven Exploration by Self-supervised Prediction

An out-of-the-box GUI tool for offline deep reinforcement learning

Learning Continuous Control in Deep Reinforcement Learning

Ramudroid, autonomous solar-powered robot to clean roads, realtime object detection and webrtc based streaming

Booklet and exam of Artificial Intelligence Master Degree at Amirkabir University of technology.

使用深度强化学习解决视觉跟踪和视觉导航问题

Pytorch reimplementation for "Gradient Surgery for Multi-Task Learning"

Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning

We reproduced DeepMind's results and implement a meta-learning (MLSH) agent which can generalize across minigames.

Using self-play, MCTS, and a deep neural network to create a hearthstone ai player

A curated list of resources about Machine Learning for Robotics

Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing

Develop ultimate AI Pokémon trainer

No description or website provided.

PyTorch implementation of some reinforcement learning algorithms: A2C, PPO, Behavioral Cloning from Observation (BCO), GAIL.

Mario AI Ensemble