https://github.com/nrjsbudhe/mendikot-ai-toolkit

AI-agent based game player | Reinforcement Learning | Monte Carlo Tree Search
https://github.com/nrjsbudhe/mendikot-ai-toolkit

artificial-intelligence mcts-algorithm reinforcement-learning

Last synced: about 1 month ago
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AI-agent based game player | Reinforcement Learning | Monte Carlo Tree Search

• Host: GitHub
• URL: https://github.com/nrjsbudhe/mendikot-ai-toolkit
• Owner: nrjsbudhe
• Created: 2024-08-18T23:35:52.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-08-18T23:51:45.000Z (4 months ago)
• Last Synced: 2024-08-19T00:47:42.872Z (4 months ago)
• Topics: artificial-intelligence, mcts-algorithm, reinforcement-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 833 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Mendikot-AI-Toolkit

## Overview

**Mendikot FAI** is a multi-player card game popular in Western India. The game consists turn-taking where each player strategically tries to win maximum tricks to win the game. The game is traditionally played in teams of 2 (people sitting in front on each other in circle).  This repository contains the source code, documentation, and related resources for the project.

This project was developed as a part of Northeastern University's Foundations of Artificial Inteligence (CS 5100) Course. 

## Documentation

Refer [Design Document ](./Project%20Environment%20Design%20Document.txt) and [Project Report](./FAI%20Report%20Final.pdf) to gain more insights about the development environment. Simulations were conducted using TEST scripts present in the [tests](./tests/) folder. 

## Getting Started

### Prerequisites

Before you begin, ensure you have met the following requirements:

- Installed Gymnassium API 

### Clone

   ```bash

   git clone https://github.com/anway0904/Mendikot_FAI.git

   cd Mendikot-AI-Toolkit