A Game of Chess using Monte Carlo Tree Search

Used the Monte Carlo Tree Search (MCTS) algorithm to simulate a game of chess that progresses by calculating the best move every single time. This model could serve as a system of reference to learn potentially best moves in different scenarios which arise in a game of chess. The webapp of the chess game is deployed using Streamlit.

Installation Steps

  https://www.anaconda.com/products/individual

Create a conda environment and activate it

  $ conda create streamlitapp
  $ conda activate streamlitapp

Install required packages from requirements.txt

  # Clone this repository and cd into it
  $ cd 
  $ pip install -r requirements.txt

Run the streamlit app

  $ streamlit run app.py  

App Screenshots