Facebook Open Sources Polygames- A Framework To Train AI Bots With Self Play

Vishal Chawla
facebook ai polygames


Polygames is a new open source AI research framework for training agents to master strategy games through self-play, rather than by studying extensive examples of successful gameplay. Because it is more flexible and has more features than previous frameworks, Polygames can help researchers with advancing and benchmarking a broad range of zero learning (ZL) techniques that don’t require training data sets.

Polygames’ architecture makes it compatible with more kinds of games — including Breakthrough, Hex, Havannah, Minishogi, Connect6, Minesweeper, Mastermind, EinStein würfelt nicht!, Nogo, and Othello — than previous systems, such as AlphaZero and ELF OpenGo. In addition to building and evaluating ZL methods across a variety of games, the tool allows researchers to study transfer learning, meaning the applicability of a model trained on one game to succeed at others. It provides a library of included games, as well as a single-file API to implement your own game.

The Facebook AI team demonstrated the effectiveness of Polygames as a training tool with strong model performances in various game competitions, including producing the first bot to beat a top-tier human player in the game 19×19 Hex. In addition to sharing the approach to building Polygames, Faceook is open-sourcing the full framework, which is available on GitHub.

See Also



Also Read: FACEBOOK RELEASES OPEN-SOURCE LIBRARY FOR 3D DEEP LEARNING: PYTORCH3D

What Do You Think?

Subscribe to our Newsletter

Get the latest updates and relevant offers by sharing your email.
Join Our Telegram Group. Be part of an engaging online community. Join Here.

Copyright Analytics India Magazine Pvt Ltd

Scroll To Top