Search is the essence
of the mind.

© rick riordan

BUt always feel free to ask...

Humans

LOCATION

4A Botkina Str.

03056 Kiev

Ukraine

CONTACT

ai.info@arvilab.com

+380 (93) 750 7715

PRIVACY POLICY

Open Alpha Zero by ARVI Lab

Here at ARVI Lab we are working hard on recreating state of the art in Deep Reinforcement learning. We are now ready to proudly present our own DRL training framework based on the Alpha Zero approach!

Train an AI to play any game with Python interface using either Alpha Go or Alpha Go Zero training process. The main goal of the project is to maximize training efficiency using regular machines and GPUs. The features of the project:

  •     Build your own neural network in Keras
  •     Optimize your neural network for inference using one line of code
  •     Distribute your self-play generation across multiple machines and GPUs via configurations
  •     Distribute your neural network training across multiple machines and GPUs using Keras distributed training or Uber's Horovod
  •     Train your AI to play games with both complete (go, chess, checkers) and incomplete informations (card games)

Getting started

The project has built-in support of two games:

We strongly recommend to read the series of articles about our project:

To get started with Alpha Zero by ARVI Lab check out the Getting started section on GitHub.

PRIVACY POLICY