Advanced Game AI with Behavior Trees in Unity 6

Coursera MOOC / Non-credit USD 49
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Advanced Game AI with Behavior Trees in Unity 6

About this course

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This advanced course offers an in-depth exploration of behavior trees in Unity 6, focusing on the implementation of AI-driven gameplay mechanics. You'll gain the skills to build complex AI systems that respond intelligently to dynamic game environments, creating immersive player experiences. Throughout the course, you'll dive into behavior tree concepts such as sequences, selectors, and node extensions, as well as advanced techniques like dynamic priority changes and agent cooperation. The course guides you through practical applications, from setting up pathfinding in Unity to building sophisticated, scalable behavior trees. You’ll also face hands-on challenges, including a cop-and-robber scenario, to test your skills in real-world conditions. By the end, you’ll be able to implement complex AI behaviors, optimize performance, and debug AI systems effectively. This course is designed for game developers who are already familiar with Unity and want to deepen their knowledge of AI systems. It’s perfect for those looking to elevate their AI development skills to an advanced level, allowing them to create intelligent, interactive gameplay experiences. No prior AI or behavior tree knowledge is required, but a strong grasp of Unity is necessary.

What you'll learn

  • Implement behavior trees in Unity 6 using sequences, selectors, and custom node extensions
  • Build AI systems that respond dynamically to changing game environments
  • Set up pathfinding systems integrated with behavior tree logic
  • Create multi-agent AI with cooperative behaviors
  • Debug and optimize AI system performance in Unity
  • Design scalable behavior tree architectures for complex gameplay

Course objectives

  • Master behavior tree implementation techniques for game AI in Unity 6
  • Develop skills in creating intelligent, interactive gameplay experiences
  • Apply advanced AI techniques including dynamic priority changes and agent cooperation
  • Build and test AI systems through practical, scenario-based challenges

Skills you'll gain

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