AxiomOfChoices

Things to try for neural networks:

General adversary network:

https://arxiv.org/pdf/1609.04802v5.pdf
Tensorflow: models

Idea:

Current models are good at maximising MSE(mean squared error) of the image, however, this metric leads to more smoothing out of the noise and thus leads to loss of detail. A new method of using the 'feature maps' of the VGG(Pretrained loss function CNN) Their GAN architecture works by getting a model to train try and estimate original image and another one trying to descriminate between the the estimate and the original. These two networks train together, the generator being scored on a combination of the VGG mentioned above and the ability of the descriminator to tell the difference.

Enhanced adversarial network:

AxiomOfChoices

Bandits

WIP

Background

You are part of a band of thieves that just successfully stole The Regent from The Louvre. As you begin your escape plan things get off the rails it’s every thief for themselves. Your mission is to snake your accomplices and steal the diamond for yourself.

Rules

Start the game with 4 cards in a hand, your goal is to end the game with The Regent (the ace of diamonds) in your possession. The winner of a round gets the regent and holds it until they lose a round. The game ends when the deck is finished.