stable-baselines
ReinforcementLearning
| stable-baselines | ReinforcementLearning | |
|---|---|---|
| 2 | 1 | |
| 277 | - | |
| 0.7% | - | |
| 0.0 | - | |
| about 1 year ago | - | |
| Python | ||
| MIT License | - |
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stable-baselines
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Does DQN from stable baselines use Dueling DQN?
Hello, I was looking at the code at https://github.com/Stable-Baselines-Team/stable-baselines/blob/master/stable_baselines/deepq/dqn.py and can't find out where Dueling DQN is being used.
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What is a wrapper in RL?
There are many wrappers available, take a look at the stable baselines codebase for some examples.
ReinforcementLearning
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Does DQN from stable baselines use Dueling DQN?
Code for https://arxiv.org/abs/1511.05952 found: https://github.com/Sharda-Borse/ReinforcementLearning
What are some alternatives?
simglucose - A Type-1 Diabetes simulator implemented in Python for Reinforcement Learning purpose
SuperSuit - A collection of wrappers for Gymnasium and PettingZoo environments (being merged into gymnasium.wrappers and pettingzoo.wrappers
dueling-dqn-Reinforcement-learning - Line plot extraction using Reinforcement learning (Dueling DQN) using Keras
rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
Tic-Tac-Toe-Gym - This is the Tic-Tac-Toe game made with Python using the PyGame library and the Gym library to implement the AI with Reinforcement Learning
learning-to-drive-in-5-minutes - Implementation of reinforcement learning approach to make a car learn to drive smoothly in minutes
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
aidoc - A simple CLI tool to generate documentation for your Python projects automatically.
voxelgym2D - Gymnasium based RL environment for 2D grid path planning
RLeXplore - RLeXplore provides stable baselines of exploration methods in reinforcement learning, such as intrinsic curiosity module (ICM), random network distillation (RND) and rewarding impact-driven exploration (RIDE).