super-mario-neat
gym-super-mario-bros
| super-mario-neat | gym-super-mario-bros | |
|---|---|---|
| 2 | 3 | |
| 94 | 663 | |
| - | - | |
| 1.8 | 0.0 | |
| almost 2 years ago | 10 months ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
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super-mario-neat
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SNES A.I. Using NEAT
After a bit of spelunking through Google, I found this Neat AI on SNES Mario: https://github.com/vivek3141/super-mario-neat
- AI Mario plays SNES
gym-super-mario-bros
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Is there a single-task, multi-scene environment using continuous action spaces like gym-super-mario-bros？
Is there a single-task, multi-scene environment using continuous action spaces? Single-task and multi-scene envs are similar to gym-super-mario-bros and CoinRun in procgen .But they are all discrete action spaces. Thank you!!!!!
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Reinforcement learning in Super mario bros
Next we wrapper nes_py.wrappers.JoypadSpace with environmental and actions
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SNES A.I. Using NEAT
A quick guess shows there is an official Mario environment, so I’ll focus on that instead. Links: https://pypi.org/project/gym-super-mario-bros/ https://github.com/Kautenja/gym-super-mario-bros
What are some alternatives?
pyneat - NEAT: NeuroEvolution of Augmenting Topologies
nes-py - A Python3 NES emulator and OpenAI Gym interface
gym-super-mario - Gym - 32 levels of original Super Mario Bros
Minigrid - Simple and easily configurable grid world environments for reinforcement learning
goNEAT - The GOLang implementation of NeuroEvolution of Augmented Topologies (NEAT) method to evolve and train Artificial Neural Networks without error back propagation
rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.
neat-python - Python implementation of the NEAT neuroevolution algorithm
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
pureples - Pure Python Library for ES-HyperNEAT. Contains implementations of HyperNEAT and ES-HyperNEAT.
gym - A toolkit for developing and comparing reinforcement learning algorithms.