PROJECT 02
Probability-Based Poker AI
PythonMonte CarloParallel programming
Overview
A poker-playing agent that uses Monte Carlo simulation to estimate win probabilities and choose an action based on the current game state.
Technical details
The agent uses Python thread pools to run simulations concurrently. The current version can simulate 100,000 hands against three opponents in approximately 14 seconds.
Why I made this
I built this as the final project for an artificial intelligence course. I still return to it occasionally to experiment and make improvements.
What I learned
- Using Monte Carlo simulations to estimate probabilities
- Implementing thread pools in Python