Deep-Reinforcement-Learning-Algorithms
deep_control
| Deep-Reinforcement-Learning-Algorithms | deep_control | |
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| 3 | 1 | |
| 903 | 100 | |
| 0.0% | 0.0% | |
| 3.6 | 1.8 | |
| about 4 years ago | over 3 years ago | |
| Jupyter Notebook | Python | |
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Deep-Reinforcement-Learning-Algorithms
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Is there a canonical simple "helloworld" neural network design? Something beyond AND/OR logic, a handful of nodes that does something mildly "useful"?
I guess the most spectacular in terms of performance/"brain size" ratio is a 2 neuron, 8 weights network https://github.com/Rafael1s/Deep-Reinforcement-Learning-Algorithms/tree/master/CartPole-Policy-Based-Hill-Climbing
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Training time of CartPole is way to long
It can be solved in 113 episodes by Hill Climbing algorithm, https://github.com/Rafael1s/Deep-Reinforcement-Learning-Algorithms/tree/master/CartPole-Policy-Based-Hill-Climbingor by Double Deep Q-Learning in 612 episodes, https://github.com/Rafael1s/Deep-Reinforcement-Learning-Algorithms/tree/master/Cartpole-Double-Deep-Q-Learning
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Need help with PyTorch script for Actor_Critic implementation of MountainCar env.
You can find the solution for MountainCar env here: https://github.com/Rafael1s/Deep-Reinforcement-Learning-Algorithms/tree/master/MountainCarContinuous-TD3This solution implemented using PyTorch. The TD3 model is the successor to DDPG algorithm using the Actor-Critic model.
deep_control
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Help on what could be wrong on my TD3?
So I am training with my own simulator from Unity connected to Open AI gym using TD3 adopted from this https://github.com/jakegrigsby/deep_control/blob/master/deep_control/td3.py
What are some alternatives?
Popular-RL-Algorithms - PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..
actorch - Deep reinforcement learning framework for fast prototyping based on PyTorch
Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020 - Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy. ICAIF 2020. Please star. [Moved to: https://github.com/AI4Finance-Foundation/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020]
deep_rl_zoo - A collection of Deep Reinforcement Learning algorithms implemented with PyTorch to solve Atari games and classic control tasks like CartPole, LunarLander, and MountainCar.
rl_lib - Series of deep reinforcement learning algorithms 🤖
autonomous-learning-library - A PyTorch library for building deep reinforcement learning agents.