Learn Game AI
Master the art of creating intelligent game characters. From classic pathfinding and state machines to modern machine learning techniques — all for free.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
What is Game AI? History, key concepts, and how AI creates believable game characters.
2. Pathfinding
A* algorithm, Dijkstra, navigation meshes, and efficient movement in game worlds.
3. Behavior Trees
Design complex AI behaviors with composable, reusable behavior tree nodes.
4. State Machines
Finite state machines, hierarchical state machines, and state-driven agent design.
5. ML in Games
Reinforcement learning, neural networks, and modern ML techniques for game AI.
6. Best Practices
Performance optimization, debugging AI, balancing difficulty, and production tips.
What You'll Learn
By the end of this course, you will be able to:
Navigate Worlds
Implement pathfinding algorithms like A* and NavMesh to move characters intelligently through game environments.
Design Behaviors
Create complex NPC behaviors using behavior trees and finite state machines for believable game characters.
Apply ML Techniques
Use reinforcement learning and neural networks to train adaptive, learning game agents.
Optimize Performance
Build efficient AI systems that run smoothly within the tight performance budgets of real-time games.