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q-learning-algorithms
This repository will aim to provide implementations of q-learning algorithms (DQN, Double-DQN, ...) using Pytorch.
I learn quite some things about reinforcement learning in the last months, and I feel like I understand much better deep-Q learning algorithms (if you want, you can check my [repo](https://github.com/thomashirtz/q-learning-algorithms). I would like to change a little bit my focus towards actor-critics algorithms now. The only thing is, I feel like in comparison to Q-learning algorithms, the explanations of the papers are not as precise as for Q-learning, and explanations on the internet diverge really greatly (e.g. the original paper does not give the A2C but only the A3C for one learner).
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- [P] I've implemented the first open-source realisation of Capacitron, an expressive VAE extension of the Tacotron 2 Text-To-Speech System and you can try it out