Playing around with OpenAI gym. Just experimenting, no serious competition intended.
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Updated
Mar 5, 2017 - Python
Playing around with OpenAI gym. Just experimenting, no serious competition intended.
A collection of Deep Reinforcement Learning algorithms implemented in tensorflow. Very extensible. High performing DQN implementation.
Open source implementation of the PAAC algorithm presented in Efficient Parallel Methods for Deep Reinforcement Learning
A PyTorch implementation of Human-Level Control through Deep Reinforcement Learning
Deep Q-learning Neural Network using tensorflow
A3C Algorithm for classic Atari games
Categorical DQN from 'A distributional Perspective on Reinforcement Learning'
Convert sc2 environment to gym-atari and play some mini-games
Get started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!
ConvNet architecture playing the Atari game Pong 👾🏓
The simplest implementation for playing Atari games using game screen as input.
Q-Learning based Reinforcement Learning implementation, make AI self-learn to play Cartpole and 3 Atari games (Boxing, Pong, Pacman)
Learning to Play Video Games using a Deep Q Network implemented with Tensorflow and ALE (Atari Learning Environment)
Tiny implementation of Deep-Q Network with Tensorflow
Pytorch implementation of the PAAC algorithm presented in Efficient Parallel Methods for Deep Reinforcement Learning https://arxiv.org/abs/1705.04862
This repository contains the code which can help us to understand how q-learning algorithm can be applied to build simple video game bot.
This gaming bot is built using simple neural network architecture
TensorFlow implementation of the two 1-step methods from "Asynchronous Deep Reinforcement Learning Methods" by Mnih et. al., 2016 for OpenAIs Gym-environment.
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