Olivaw: Mastering Othello Without Human Knowledge, nor a Fortune

In this article, we introduce
Olivaw
, an artificial intelligence
Othello
player adopting the design principles of the famous AlphaGo programs. The main motivation behind
Olivaw
is to attain exceptional competence in a nontrivial board game at a tiny fraction of the cost of its illustrious predecessors. In this article, we show how the AlphaGo Zero’s paradigm can be successfully applied to the popular game of
Othello
using only commodity hardware and free cloud services. While being simpler than
Chess
or
Go
,
Othello
maintains a considerable search space and difficulty in evaluating board positions. To achieve this result,
Olivaw
implements some improvements inspired by recent works to accelerate the standard AlphaGo Zero learning process. The main modification implies doubling the positions collected per game during the training phase, by including also positions not played but largely explored by the agent. We tested the strength of
Olivaw
in three different ways: by pitting it against Edax, considered by the strongest open-source
Othello
engine, by playing anonymous games on the web platform OthelloQuest, and, finally, in two in-person matches against top-notch human players: a national champion and a former world champion.