A deep learning chess bot that uses CNN and RNN to play chess. Architecture includes a dense layer, reshape layer, convolutional layer, max pooling layer, flatten layer, LSTM layer, and another dense layer. NeuroChess training (currently in Beta) and optimizations are in development.
- tfjs-node
- yarn
- ReactDOM
- Chess.js
- Chessboardjsx
- @tensorflow/tfjs
- @tensorflow/tfjs-layers
- PapaParse
- Typescript
- encoding/json
- net/http
- github.com/notnil/chess package
- Node.js
- npm 'npm - v'
- 'npm install'
- TypeScript 'npm install -g typescript'
- React 'npm install -g create-react-app'
- TensorFlow.js 'npm install @tensorflow/tfjs'
- Chess.js 'npm install chess.js'
- Chessboardjsx 'npm install react-chessboardjsx'
- express and http-proxy-middleware 'npm install express http-proxy-middleware'
Development
- Clone the repository and install prerequisites.
- Navigate to the project directory via the terminal.
- Run 'yarn install' for dependencies and 'yarn start' for the development server.
- For the app, navigate to 'http://localhost:3000'
Production
- npm run build
- npm run start-proxy (Go server requests go to 'http://localhost:8080/api'
- Start the server through the command 'yarn start-proxy'. API requests go to port 5000.