adarshsankarrs/AI-Chess-Game

To simulate a chess game that advances by determining the optimal move each and every time, the Monte Carlo Tree Search (MCTS) algorithm was employed. The model has the ability to function as a framework for determining the optimal moves in various chess scenarios. Streamlit is used in the deployment of the chess webapp.

A Chess Game using Monte Carlo Tree Search algorithm .

Monte Carlo Tree Search (MCTS) algorithm is used to calculate the optimal move each and every time, simulating a progressive game of chess. This model could be used as a framework to figure out the best moves to make in various chess game conditions. The chess webapp is implemented with 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