This Repository consists of a Deep Convolutional-Variational Autoencoder (CNN-VAE) made in Python using Tensorflow 1.x

Major Inspiration for implementation was taken from Ha and Schmidhuber, "Recurrent World Models Facilitate Policy Evolution", 2018. .

Although currently a stand-alone implementation for general use, this model will be accompanied by a Mixed Density Recurrent Neural Network and Genetic Algorithms in my attempt to implement this paper presented at NeurIPS 2018.

The main model has only 2 dependencies, Numpy and Tensorflow

For Numpy (On Linux/MacOS);

pip3 install numpy

OR

conda install numpy

For Numpy (On Windows);

pip install numpy

OR

conda install numpy

For Tensorflow (This model uses some deprecated function calls, so you need to have tensorflow version <= 1.5

On Linux/MacOS;

pip3 install tensorflow==1.12

OR

conda install tensorflow==1.12

On Windows;

pip install tensorflow==1.12

OR

conda install tensorflow==1.12