A Gentle Introduction to Reinforcement Learning

An introductory tutorial on reinforcement learning through a multi-agent taxi environment, explaining how agents learn by receiving feedback from their environment. Covers Q-learning fundamentals including the Bellman equation and epsilon-greedy exploration strategies.