With RLogue, you can explore how Reinforcement Learning algorithms behave in a simple and intuitive environment. This simulator features six different RL agents, using algorithms such as Value Iteration, Q-learning, SARSA, MBIE-EB and policies such as epsilon-greedy and SoftMax. There is also a 'game' mode, where you will race against the AI to reach the goal first, learning to navigate in an unknown space. The project has been created using Unity3D. This project was created for the Reinforcement Learning PhD course at POLIMI.