This report deals with reinforcement learning, a branch of machine learning. The report examines whether a Q-learning agent can learn to play the board game Hare and Hounds. By implementing the Q-learning algorithm, analysis has been completed on different aspects of the learning process. The experiments performed to examine the Q-learning is one test of the learning parameters, one test against a simple strategy and one test that shows the Q-learning convergence. The investigations show that Q-learning is well suited for learning to play the board game Hare and Hounds.