Papayoo-AI-Agent

By LeeAnne King, Sara Francis and Dominic Lau

Papayoo-AI-Agent is a Python project that implements an artificial intelligence agent to play the card game Papayoo. The agent uses various strategies and algorithms to analyze the game state and make optimal decisions, enabling automated gameplay and experimentation with different AI approaches in a simulated Papayoo environment.

Project Description

This repository contains an AI agent capable of playing Papayoo, a trick-taking card game where players aim to avoid certain penalty cards. The agent incorporates various algorithms to analyze the game state, predict opponents' moves, and select optimal actions. The project can be used for research, personal learning, or as a foundation for developing more advanced game-playing agents.

Skills Learned

• Python Programming: Structuring code, using classes, and managing game logic.
• Artificial Intelligence: Implementing decision-making algorithms and strategies.
• Game Theory: Analyzing outcomes and optimizing decisions in adversarial environments.
• Simulation: Creating and running simulations to test agent performance.
• Testing and Debugging: Writing unit tests and debugging complex logic.
• Documentation: Documenting code and usage for clarity and maintainability.