Heads-Up Hold’em: Technical Report

In today’s world, Artificial Intelligence exists in every game we play. It was a challenge for computer scientists to beat the professional players since computers were invented. Many games are deterministic perfect information games like chess or checkers where there is no chance and there is no any hidden information from the opponent. This thesis investigates non-deterministic imperfect information games like poker that are very popular in real world. There exists a technique that calculates the strategies over time to win the player by reaching the Nash equilibrium. Poker is currently the world’s most played card game. Hundreds of thousands of people play poker every day, and can play in a real-life environment or over the internet using a distributed application running a simulation of the game. One of the biggest reasons for poker’s recent success is its fundamental dynamics. The ‘hidden’ elements of the game means players must observe their opponent’s characteristics to be able to arrive at good decisions, given their options. A very good poker player will consistently dominate a sub-optimal opponent, although stochastic elements apply heavy statistical variation to the game, allowing weak players to win occasionally. The game of poker offers a well-defined domain in which to investigate some fundamental issues in computing science, such as how to handle deliberate misinformation, and how to make intelligent guesses based on partial knowledge. This project will aim to investigate what Artificial Intelligence techniques can be applied to the domain in order to play up to a human standard of decision making. The findings of the research have application beyond the realm of poker, and can be applied to financial, weather and military domains, or more generally, any domain with a nondeterministic outcome that incorporates stochastic elements