AI Agents in Gaming: From NPCs to Strategic AI

• Basic understanding of programming concepts
• Familiarity with game development tools or frameworks
• Basic knowledge of AI principles

Audience

• Game developers
• AI enthusiasts

AI agents have revolutionized gaming by providing intelligent and responsive behaviors, from non-playable characters (NPCs) to strategic decision-making systems. This course explores the creation of AI agents in gaming, delving into essential topics such as decision trees, pathfinding algorithms, and reinforcement learning techniques.

This instructor-led, live training (online or onsite) is aimed at intermediate-level game developers and AI enthusiasts who wish to integrate AI agents into gaming applications effectively.

By the end of this training, participants will be able to:

• Understand the role of AI agents in modern gaming.
• Develop decision-making systems using decision trees and finite state machines.
• Implement pathfinding algorithms such as A* for in-game navigation.
• Apply reinforcement learning techniques to create adaptive AI behaviors.
• Optimize AI performance for real-time gaming environments.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to AI in Gaming

• Overview of AI applications in games
• Types of AI agents: NPCs, strategic AI, and more
• Key concepts in game AI development

Decision-Making Systems

• Implementing decision trees for simple AI logic
• Finite state machines for complex behaviors
• Behavior trees and modular AI design

Pathfinding and Navigation

• Understanding pathfinding algorithms
• Implementing A* algorithm for in-game navigation
• Optimizing pathfinding for large maps

Reinforcement Learning in Games

• Introduction to reinforcement learning concepts
• Training AI agents using Q-learning and deep Q-networks
• Designing reward structures for adaptive behaviors

Optimizing AI Performance

• Techniques for real-time AI performance optimization
• Managing resources and prioritizing AI tasks
• Debugging and troubleshooting AI systems

Advanced AI Techniques

• Procedural content generation with AI
• Simulating player-like behaviors
• Integrating AI with multiplayer gaming

Future Trends in Game AI

• AI and machine learning in next-generation gaming
• Ethical considerations in game AI
• Exploring AI-driven storytelling and narrative design

Summary and Next Steps