TensorFlow2.0-for-Deep-Reinforcement-Learning
tensorforce
TensorFlow2.0-for-Deep-Reinforcement-Learning | tensorforce | |
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1 | 1 | |
81 | 3,281 | |
- | 0.2% | |
0.0 | 3.0 | |
8 months ago | 25 days ago | |
Python | Python | |
- | Apache License 2.0 |
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TensorFlow2.0-for-Deep-Reinforcement-Learning
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Beginner attempting to implement Noisy DQN
I forgot to say that I'm using tensorflow, nevertheless I managed to find a git implementation for tensorflow 2 of the noisy dense layer (https://github.com/Huixxi/TensorFlow2.0-for-Deep-Reinforcement-Learning/blob/master/07_noisynet.py) and tried to adapt it to my needs.
tensorforce
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Advice on doing RL for Settlers of Catan?
The most promising approach has been using the TensorForce framework (https://github.com/tensorforce/tensorforce) with a custom environment that represents a simpler game (1v1 against a bot that chooses actions randomly, no trading between players, and fixing discarding to be done automatically and at random).
What are some alternatives?
pytorch-a2c-ppo-acktr-gail - PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
DeepRL-TensorFlow2 - 🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
trax - Trax — Deep Learning with Clear Code and Speed
agents - TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
chainerrl - ChainerRL is a deep reinforcement learning library built on top of Chainer.
deepdrive - Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving
Deep-Reinforcement-Learning-Hands-On - Hands-on Deep Reinforcement Learning, published by Packt
action-branching-agents - (AAAI 2018) Action Branching Architectures for Deep Reinforcement Learning