Reinforcement Learning for Super Mario Bros using A3C on GPU
-
Updated
Apr 5, 2018 - Python
Reinforcement Learning for Super Mario Bros using A3C on GPU
Several approaches using deep reinforcement learning to play Super Mario Bros.
A Reinforcement Learning agent that learns to play Super Mario Bros.
Deep-Reinforcement-Learning with A3C in 'Super Mario Bros' (NES, 1985)
Play games without touching keyboard
IERG5350 Course Project, Fall 2020
MuZero for Super Mario Bros
Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
Reinforcement learning (PPO) plays Mario.
Durham University, Dissertation: 1st - 92. Additional Materials and Codebase for the paper: Combining Recent Advances in Reinforcement Learning for Super Mario Bros. - Recurrent Replay Deeper Denser Distributed DQN+ (R2D4+).
Official repository for "TOAD-GAN: Coherent Style Level Generation from a Single Example" by Maren Awiszus, Frederik Schubert and Bodo Rosenhahn.
This program evolves an AI using the NEAT algorithm to play Super Mario Bros.
SMRP (Or super Mario retexturing program) is a program made to allow you to play SM64 and swap faces, texture packs and more without having to touch any files yourself.
Random network distillation on Montezuma's Revenge and Super Mario Bros.
Reinforcement Learning PPO Super Mario Bros Agent
🍄 Reinforcement Learning agent for Super Mario Bros
MarioPPO implementation uses the TensorFlow machine learning platform
Add a description, image, and links to the super-mario-bros topic page so that developers can more easily learn about it.
To associate your repository with the super-mario-bros topic, visit your repo's landing page and select "manage topics."