React Go Game for Two Players

What is a "Go Game"?

“Go is an abstract strategy board game for two players, in which the aim is to surround more territory than the opponent. The game was invented in China more than 2,500 years ago and is believed to be the oldest board game continuously played to the present day.” Source: Wikipedia

Comparing Go To Chess

Like Chess, Go is a two person board game where chance plays no role in deciding the outcome of the game. Both games have steep learning curves and players can spend decades improving their skills.

That said, an argument can be made that Go is considerably more difficult for computer algorithms to “learn” and it has proven to be more difficult for computers to compete with master Go players.

It required approximately 20 more years for computer-based strategies to compete in Go than in Chess. Google Deep Mind defeated world the champion Go Player in 2016 (approximately 20 years after computers began to dominate human chess players). It was not possible for computer algorithms to compete with human Go champions until machine learning technologies reached an adequate level of maturity.

Here is one comparison that helps explain why Go is more challenging for computer algorithms than Chess. There are just vastly more possible moves in Go than in chess. The following compares just the possible options in just the first two moves of each game.

A count of possible first and second moves in chess = 20 x 20 = 400 possible moves in the first two turns.

A count of possible first and second moves in Go = 362 x 361 = 130,682 possible moves in the first two turns.

A rough approximation of the number of all the possible moves in a Go game is 362! (362 factorial = 362 x 361 x 360 x 359 … 4 x 3 x 2 x 1). It is a really big number in the neighborhood of 5 followed by 770 zeros. That is considerably more than the number of atoms in the known universe, in case you were wondering.

Thus, the “brute force” mapping of all useful moves as has been practiced in Chess, is not feasible in Go.

The Go Game for Two Players as a React Responsive Web Application

Below is the responsive view as seen on a wide desktop.

And here is the responsive view on a smart phone.

This project provides the following challenges to provoke deep learning:

• Spatial algorithms to score each game move
• State Management to share information between the 361 intersections and the containing board
• Push messaging to alert users to the play of opponents and to support chat
• Authorization and authentication
• NoSql Document Database
• Responsive Web Design
• React, TypeScript, HTML5, Chakra UI, Zustand state management (Redux light?), CSS

Features of the Project

• Firebase Authentication - SAML and generic OpenID Connect - (Google)
• Registering new users
• Users can create new matches by choosing opponents and stone colors
• Users can choose among available matches in progress
• Users can place stones (move) when it is their turn or pass
• The most recent move is marked with move number (see '100' in the images)
• Users are prompted to confirm moves and passes
• Users can live-chat while playing a Go Game

Features Not Included

The following features are not included but may be added at a future date.

• Playing against the computer (AI)
• Final scoring of the game to determine the winner In a Go game, this is a non-trivial feature.
• Review (stepping through) the game moves one at a time.

If you are not familiar with the rules of the Game of Go, you can try this tutorial.

A Go Game Tutorial: This tutorial was chosen because of its educational value. No product endorsement is implied.

Continuous Improvement

This project provides the following opportunities for continuous improvement.

• Add Semantic Versioning Tags to Git Repository
• Improve Unit Test Coverage
• Code review looking for opportunities to improve (I will find plenty)
• User Documentation and Help including Go Game rules

Future Forks (planned major revisions and new versions)

An adequately rich problem domain project can be re-used to exercise more skillsets. The following are the future plans for this project.

• Replace the Firebase API with AWS Serverless Lambdas backed by DynamoDB
• Host the Go Game in an AWS EC2 instance and/or Dockerize with AWS Fargate
• Re-engineer UI with React Native
• Add AI opponent

Past Iterations

• Two console Go Games - one in C# (2010) and one in Nodejs (2023)

• Angular 8 Go Game - 2019
  • Azure Active Directory B2C
  • Azure SQL
  • Azure DevOps - CI/CD
  • Docker

• ASP.NET MVC Go Game (~2015) No image available
  • ASP.NET WEB API
  • Azure SQL
• ASP.NET Go Game (~2010) No image available

You can visit the GitHub repository for this project.