AI Learns Minecraft PvP (Reinforcement Learning + Behavior Cloning)

Building a neural network capable of dominating Minecraft PvP presents a massive systems engineering challenge. In this devlog, we break down the entire pipeline of training an autonomous AI agent to handle high-speed diamond sword combat, moving from initial imitation learning to fine-tuning the model's real-time decision-making loops. Instead of relying on basic macros or cheat clients, we look under the hood at the reward functions, logic frameworks, and feature engineering required to teach a bot how to sprint-hit, execute flawless combos, strafe around enemies, and react to unpredictable human movement in a dynamic arena simulation. Whether you are a machine learning engineer interested in reinforcement learning or a Minecraft player fascinated by game automation, this is the complete technical breakdown of what happens when artificial intelligence enters the PvP arena. 0:00 Intro 0:52 Behavior Cloning 2:57 Beginning of Reinforcement Learning 4:33 Feature Engineering 8:25 Last Phase of Training 9:01 Is This Cheating? 10:00 Human Fights 10:45 Reflections Background footage from Pexels, Pixabay, Adobe Stock, Veo Music by Karl Casey @ White Bat Audio