Implementation of a DDQN to play SMB for the NES.
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Updated
Jun 21, 2024 - Python
Implementation of a DDQN to play SMB for the NES.
Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros
Reinforcement learning algorithm that blends the N-th order Markov property with abstract MDPs, PPO, and a hybrid model-free/model-based approach.
A reinforcement learning project designed to learn and complete the original Super Mario Bros.
GUI for TOAD-GAN, a PCG-ML algorithm for Token-based Super Mario Bros. Levels.
A primeira fase do jogo Super Mario Bros
AI Python Framework for Super Mario Bros.
An OpenAI Gym interface to Super Mario Bros. & Super Mario Bros. 2 (Lost Levels) on The NES
A remake of the Super Mario Bros game written in Python using Pygame
A minimal VAE trained on Super Mario Bros levels.
MarioPPO implementation uses the TensorFlow machine learning platform
🍄 Reinforcement Learning agent for Super Mario Bros
Reinforcement Learning PPO Super Mario Bros Agent
Random network distillation on Montezuma's Revenge and 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.
This program evolves an AI using the NEAT algorithm to play Super Mario Bros.
Official repository for "TOAD-GAN: Coherent Style Level Generation from a Single Example" by Maren Awiszus, Frederik Schubert and Bodo Rosenhahn.
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+).
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