dueling-dqn-Reinforcement-learning
stable-baselines
| dueling-dqn-Reinforcement-learning | stable-baselines | |
|---|---|---|
| 1 | 2 | |
| 3 | 277 | |
| - | 0.0% | |
| 10.0 | 0.0 | |
| almost 6 years ago | about 1 year ago | |
| Python | Python | |
| - | MIT License |
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dueling-dqn-Reinforcement-learning
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Does DQN from stable baselines use Dueling DQN?
Code for https://arxiv.org/abs/1511.06581 found: https://github.com/zynk13/dueling-dqn-Reinforcement-learning
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.
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
rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
ReinforcementLearning
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).