SNES Games

4 papers with code • 5 benchmarks • 1 datasets

The task is to train an agent to play SNES games such as Super Mario.

( Image credit: Large-Scale Study of Curiosity-Driven Learning )


Most implemented papers

Large-Scale Study of Curiosity-Driven Learning

openai/large-scale-curiosity ICLR 2019

However, annotating each environment with hand-designed, dense rewards is not scalable, motivating the need for developing reward functions that are intrinsic to the agent.

Evolving Mario Levels in the Latent Space of a Deep Convolutional Generative Adversarial Network

TheHedgeify/DagstuhlGAN 2 May 2018

This paper trains a GAN to generate levels for Super Mario Bros using a level from the Video Game Level Corpus.

Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks

fabiopardo/qmap ICLR 2019

Being able to reach any desired location in the environment can be a valuable asset for an agent.

Playing SNES in the Retro Learning Environment

nadavbh12/Retro-Learning-Environment 7 Nov 2016

The environment is expandable, allowing for more video games and consoles to be easily added to the environment, while maintaining the same interface as ALE.