Game AI - Classical AI in Modern Videogames

🎮 Game AI

Game AI is the ultimate course on Classical AI in modern videogames, covering everything you need to know, from Behaviour Trees to Neural Networks. Taught by a Senior Lecturer and Game Developer, with over a decade of experience.

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Course curriculum

1. Course Trailer
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2. 📦 Unity Package v4.0
1. Overview
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2. 1. Introduction
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3. 2. Defining Artificial Intelligence
4. 3. PONG: Reactive & Predictive AI
5. 4. Pac-Man: Intelligence vs Personality
6. Take-Home Messages
7. 📝 References
1. Overview
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2. 1. Introduction
3. 2. History of Game AI
4. 3. AI Before Computers
5. Take-Home Messages
6. 📝 References
7. 📚 Additional resources
1. Overview
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2. 1. Introduction
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3. 2. Pac-Man's Ghost AI
4. 3. Extensions
5. 4. Implementation
6. Take-Home Messages
7. 📝 References
8. 📚 Additional resources
1. Overview
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2. 1. Introduction
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3. 2. Structure
4. 3. Extensions
5. 4. Games
6. 5. Implementation
7. Take-Home Messages
8. 📝 References
9. 📚 Additional resources
10. 📄 Behaviour Tree Library
1. Overview
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2. 1. Introduction
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3. 2. Path to Pathfinding
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4. 3. Breadth-First Search
5. 4. Depth-First Search
6. 5. Dijkstra's Algorithm
7. 6. A*
8. 7. From Pathfinding to AI
9. 8. Implementation
10. Take-Home Messages
11. 📝 References
12. 📚 Additional resources
13. 📄 Pathfinding Library
1. Snake Assignment
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2. 📝 Assignment Brief
3. 🪪 User ID
4. 📦 Unity Package v4.0
5. 📮 Assignment Submission
1. Overview
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2. 1. Introduction
3. 2. Linear Algebra
4. 3. Kinematics
5. 4. Seek & Flee
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6. 5. Arrival & Leave
7. 6. Other steering behaviours
8. 7. Combining steering behaviours
9. Take Home Messages
10. 📝 References
11. 📚 Additional resources
1. Overview
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2. 1. Introduction
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3. 2. Flocking Behaviours
4. 3. Collision Avoidance
5. 4. Particle Life
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6. 5. Cellular Automata
7. Take-Home Messages
8. 📝 References
9. 📚 Additional resources
1. Overview
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2. 1. Utility Systems
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3. 2. Expected Utility
4. 3. Action Selection
5. 4. Utility Curves
6. 5. Chess AI
7. 6. Tetris AI
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8. Take-Home Messages
9. 📝 References
10. 📚 Additional resources
1. 📝 Assignment Brief
2. 🪪 User ID
3. 📦 Unity Package v4.0
4. 📮 Assignment Submission
1. Overview
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2. 1. Introduction
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3. 2. From Pathfinding to Planning
4. 3. GOAP: Goal-Oriented Action Planning
5. 4. STRIPS: Stanford Research Institute Problem Solver
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6. 5. Implementation
7. Take-Home Message
8. 📝 References
9. 📚 Additional resources
10. 📄 GOAP Library
1. Overview
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2. 1. Introduction
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3. 2. Minimax
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4. 3. Alpha-Beta Pruning
5. 4. Multi-Armed Banding Problem
6. 5. Monte Carlo Tree Search
7. 6. Go AI
8. 7. Implementation
9. Take-Home Messages
10. 📝 References
11. 📚 Additional resources
1. Overview
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2. 1. Content Warning
3. 2. Introduction
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4. 3. Evolution by Natural Selection
5. 4. Evolutionary Algorithms
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6. 5. Genetic Algorithms
7. 6. Implementation
8. Take-Home Message
9. 📝 References
10. 📚 Additional resources
11. 📄 Evolution Library
1. Overview
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2. 1. Introduction
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3. 2. Regression Analysis
4. 3. Linear Regression
5. 4. Non-Linear Regression
6. 5. Universal Approximation Theorem
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7. 6. Backpropagation
8. Take-Home Messages
9. 📝 References
10. 📚 Additional resources
11. 📄 Neural Network Library

About this course

$199.99
129 lessons
23.5 hours of video content

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Alan Zucconi

🎮 Game AI

Course curriculum

🧔🏻‍♂️ 00 ● Presentation

🤖 01 ● Introduction

📜 02 ● History of AI

🔄 03 ● Finite State Machines

🌳 04 ● Behaviour Trees

🗺️ 05 ● Pathfinding

🐍 CW1 ● Snake Assignment

🚗 06 ● Steering Behaviours

🐦 07 ● Emergent Behaviours

📊 08 ● Utility Theory

🧱 CW2 ● Tetris Assignment

📝 09 ● Planning

🔎 10 ● Tree Search

🧬 11 ● Evolution

🧠 12 ● Neural Networks

About this course

Discover your potential, starting today