RL agent that is trained to catch moving pucks in a complex environment, with DQN, AC, A2C and more.
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Updated
Oct 9, 2019 - Python
RL agent that is trained to catch moving pucks in a complex environment, with DQN, AC, A2C and more.
PyTorch implementation of Asynchronous (and Synchronous) Advantage Actor Critic
Example A2C implementation with ReLAx
First Place Reinforcement Learning solution code and a writeup for the AI RoboSoccer Competition.
The pytorch implemetation of a2c
Multi-task learning with Advantage Actor Critic and sharing experience
This repository contains my assignment solutions for the Deep Learning course (M2177.003100_002) offered by Seoul National University (Fall 2019).
Training a Reinforcement Learning Agent to Play Flappy Bird.
Solving CartPole-v1 environment in Keras with Advantage Actor Critic (A2C) algorithm an Deep Reinforcement Learning algorithm
Implementations of deep reinforcement learning algorithms.
It's a Raspberry Pi Pokémon that gamifies WiFi Hacking by learning from its surrounding WiFi environment utilising deep Reinforcement Learning.
Code for Hands On Intelligent Agents with OpenAI Gym book to get started and learn to build deep reinforcement learning agents using PyTorch
Deep reinforcement learning package for torch7
Official implementation of the AAAI 2021 paper Deep Bayesian Quadrature Policy Optimization.
The friendly robot that beats you in Yahtzee 🤖 🎲
MLP-framework (pure numpy) and DDQN-framework for OpenAI's Gym games. +test code for PPO added. +Hindsight Experience Replay(HER) bitflip-DQN example. +prioritized replay.
[ICRA'23] Demonstration-Guided Reinforcement Learning with Efficient Exploration for Task Automation of Surgical Robot
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
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