procgen
gym-super-mario-bros
| procgen | gym-super-mario-bros | |
|---|---|---|
| 3 | 3 | |
| 973 | 661 | |
| 0.5% | - | |
| 0.0 | 0.0 | |
| 4 months ago | 9 months ago | |
| C++ | Python | |
| MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
procgen
-
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!!!!!
-
My AI projects don't seem to learn, even if I use an official Gym environment. (Python 3.7)
And now "bigfish" from the procgen Gym environments, tested on Stable Baselines 3. (No success)
-
Any tutorial on how to create RL C++ environments?
It's not exactly a tutorial, but OpenSpiel has C++ environments ported to Python that are relatively simple and easy to understand. Procgen would be a more complicated reference to check out as well.
gym-super-mario-bros
-
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!!!!!
-
Reinforcement learning in Super mario bros
Next we wrapper nes_py.wrappers.JoypadSpace with environmental and actions
-
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?
tiny-differentiable-simulator - Tiny Differentiable Simulator is a header-only C++ and CUDA physics library for reinforcement learning and robotics with zero dependencies.
nes-py - A Python3 NES emulator and OpenAI Gym interface
open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
Minigrid - Simple and easily configurable grid world environments for reinforcement learning
ReinforcementLearning.jl - A reinforcement learning package for Julia
super-mario-neat - This program evolves an AI using the NEAT algorithm to play Super Mario Bros.
brax - Massively parallel rigidbody physics simulation on accelerator hardware.
rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.
Numba - NumPy aware dynamic Python compiler using LLVM
gym-super-mario - Gym - 32 levels of original Super Mario Bros