Connect-4 Game with Q-Learning Algorithm

Created by @karakusfurkan and @ihsankavalci and done as a graduation project.

Q-learning is a model-free reinforcement learning algorithm. The goal of Q-learning is to learn a policy, which tells an agent what action to take under what circumstances. It does not require a model (hence the connotation "model-free") of the environment, and it can handle problems with stochastic transitions and rewards, without requiring adaptations.

Image of QL Formula

source: https://en.wikipedia.org/wiki/Q-learning

In project we found/used min-max algorithm via internet to test our train set.