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Course Outline

Introduction to AI in Gaming

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

Decision-Making Systems

  • Implementing decision trees for straightforward AI logic.
  • Utilizing finite state machines for complex behaviors.
  • Employing behavior trees and modular AI design.

Pathfinding and Navigation

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

Reinforcement Learning in Games

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

Optimizing AI Performance

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

Advanced AI Techniques

  • Procedural content generation using 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

Requirements

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

Audience

  • Game developers.
  • AI enthusiasts.
 14 Hours

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