Module 1: Introduction to AI in Games

1.1 What is AI?

1.2 Evolution of AI in the Gaming Industry

1.3 Types of AI in Games

1.4 Benefits, Challenges, and Innovations in Game AI

Module 2: Game Design Principles using AI

2.1 Understanding Game Mechanics and Player Experience

2.2 Role of AI in Gameplay and Narrative Design

2.3 Designing Game Environments for AI Interaction

2.4 AI-Driven Behaviour vs Traditional Scripted Logic

2.5 Case Study: Dynamic AI and Narrative Adaptation in Middle-earth: Shadow of Mordor

2.6 Hands-On Exercise: Designing Adaptive NPC Behaviour and Environment Interaction

Module 3: Foundations of AI in Gaming

3.1 Core AI Concepts for Gaming

3.2 Search Algorithms and Pathfinding

3.3 AI Behaviour Modelling and Procedural Content Generation (PCG)

3.4 Introduction to Machine Learning and Reinforcement Learning

3.5 Case Study: AI in Minecraft — Procedural Content Generation and Agent Navigation

3.6 Hands-On: Implementing A* Pathfinding and FSM for NPC Behaviour

Module 4: Reinforcement Learning Fundamentals

4.1 Core Concepts: States, Actions, Rewards, Policies, Q-Learning:

4.2 Exploration versus Exploitation in Learning Systems:

4.3 Overview of Deep Q Networks (DQN) and Policy Gradient Methods

4.4 Case Study: Reinforcement Learning in DeepMind’s AlphaGo

4.5 Hands-On: Train a Reinforcement Learning Model on OpenAI Gym’s GridWorld

Module 5: Planning and Decision Making in Games

5.1 Minimax Algorithm and Alpha-Beta Pruning

5.2 Monte Carlo Tree Search (MCTS)

5.3 Applications in Board Games and Real-Time Strategy (RTS) Games

5.4 Case Study: Strategic AI in StarCraft II – Combining Planning Algorithms for Real-Time Strategy

5.5 Hands-on Implementation: Guides on implementing the Minimax algorithm for Tic-Tac-Toe

Module 6: AI Techniques in 2D/3D Virtual Gaming Environments Basic

6.1 Overview of 2D and 3D Game Environments

6.2 Environment Representation Techniques

6.3 Navigation and Pathfinding in 2D/3D Spaces

6.4 Interaction and Behaviour Systems in Virtual Environments

6.5 Case Study: Navigation and Interaction AI in The Legend of Zelda: Breath of the Wild

6.6 Hands-On: Building Basic Navigation and Interaction in 2D and 3D Game Environments

Module 7: Adaptive Systems and Dynamic Difficulty

7.1 Adaptive Systems Overview

7.2 Dynamic Difficulty Adjustment (DDA) Principles

7.3 Adaptive Storytelling, Personalisation, and Player Profiling

7.4 AI Techniques in Adaptive Systems

7.5 Implementation Strategies and Tools

7.6 Case Study: Dynamic Enemy Management and Replayability with Left 4 Dead’s AI Director

7.7 Hands-On: Developing an Adaptive Dynamic Difficulty System in Unity

Module 8: Future of AI in Gaming

8.1 Generalist AI Agents and Transfer Learning

8.2 AI-Powered Game Design and Testing Tools

8.3 Ethical Considerations and AI Transparency

8.4 Emerging Technologies: VR/AR AI and AI in Esports Coaching

Module 9: Capstone Project