gym-super-mario-bros
gym
| gym-super-mario-bros | gym | |
|---|---|---|
| 3 | 96 | |
| 663 | 33,966 | |
| - | 0.6% | |
| 0.0 | 0.0 | |
| 10 months ago | 19 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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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
gym
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OpenAI Acquires Global Illumination
A co-founder announced they disbanded their robots team a couple years ago: https://venturebeat.com/business/openai-disbands-its-robotic...
That was the same time they depreciated OpenAI Gym: https://github.com/openai/gym
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Shimmy 1.0: Gymnasium & PettingZoo bindings for popular external RL environments
This includes single-agent Gymnasium wrappers for DM Control, DM Lab, Behavior Suite, Arcade Learning Environment, OpenAI Gym V21 & V26. Multi-agent PettingZoo wrappers support DM Control Soccer, OpenSpiel and Melting Pot. For more information, read the release notes here:
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Some confusion about variables and functions in mujoco-py
When I browse fetch_env.py, I have a question about the following code snippet:
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pip install stable-baselines3[extra]
Nvm, this works for me '!pip install setuptools==65.5.0' Source: https://github.com/openai/gym/issues/3176
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[P] Reinforcement learning evolutionary hyperparameter optimization - 10x speed up
how would this interact/compare with https://github.com/openai/gym?
- What has replaced OpenAI Retro Gym?
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Understanding Reinforcement Learning
If you'd like to learn more about reinforcement learning or play with a number of samples in controlled environments, I highly recommend you look at the documentation for OpenAI's Gym library and particularly the basic usage page. OpenAI's Gym provides a standardized environment for performing reinforcement learning on classic Atari games and a few other platforms and should be an educational resource. If you'd like a more detailed example, check out this tutorial on Paperspace's blog.
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Using the cross-entropy method to solve Frozen Lake
Frozen Lake is an OpenAI Gym environment in which an agent is rewarded for traversing a frozen surface from a start position to a goal position without falling through any perilous holes in the ice.
- Is there a publicly available state space model for the Lunar Lander environment?
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How to Create a Behavioral Cloning Bot to Play Online Games?
typically a more relaxed approach is taken via reinforcement learning, but it requires that you can simulate the game via a given gamestate. take a look at e.g. https://www.gymlibrary.dev/
What are some alternatives?
nes-py - A Python3 NES emulator and OpenAI Gym interface
ml-agents - The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
Minigrid - Simple and easily configurable grid world environments for reinforcement learning
carla - Open-source simulator for autonomous driving research.
super-mario-neat - This program evolves an AI using the NEAT algorithm to play Super Mario Bros.
tensorflow - An Open Source Machine Learning Framework for Everyone
rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.
dm_control - Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
gym-super-mario - Gym - 32 levels of original Super Mario Bros
open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros