Chainerrl Alternatives
Similar projects and alternatives to chainerrl
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machin
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
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deep-q-learning
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras (by keon)
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SonarLint
Clean code begins in your IDE with SonarLint. Up your coding game and discover issues early. SonarLint is a free plugin that helps you find & fix bugs and security issues from the moment you start writing code. Install from your favorite IDE marketplace today.
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TensorLayer
Deep Learning and Reinforcement Learning Library for Scientists and Engineers
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Deep-Reinforcement-Learning-Hands-On
Hands-on Deep Reinforcement Learning, published by Packt
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TensorFlow2.0-for-Deep-Reinforcement-Learning
TensorFlow 2.0 for Deep Reinforcement Learning. :octopus:
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DeepLearning
Contains all my works, references for deep learning (by harshraj22)
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Scout APM
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
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fundamentalRL
educational codebase demonstrating some of the most common RL algorithms
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DeepRL-TensorFlow2
🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
chainerrl reviews and mentions
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Help with my PyTorch implementation of PPO
Code for https://arxiv.org/abs/1709.06560 found: https://github.com/chainer/chainerrl
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Any working Acer implementation for continuous action space?
I implemented my version of Acer that supports discrete action space. I need to add an extension that supports continuous action space. I've seen a couple of implementations here and here. The first doesn't work for PongNoFrameskip-v4 and the other doesn't work in macOS.
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Beginner attempting to implement Noisy DQN
I tried all the versions I found and in most of them the network couldn't even learn to set the sigma as 0 (or close). The only implementation where I actually got improvement was by changing the noise directly when calling the noisy layers in this git. I don't know if this is the correct way but it sure showed good results.
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chainer/chainerrl is an open source project licensed under MIT License which is an OSI approved license.
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