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Artificial Intelligence in Unreal Engine 5

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Artificial Intelligence in Unreal Engine 5

包含在 Coursera Plus

深入了解一个主题并学习基础知识。
中级 等级

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2 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度
深入了解一个主题并学习基础知识。
中级 等级

推荐体验

2 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Discover the fundamentals of AI development in video games

  • Understand and implement key components of the Unreal Engine AI framework

  • Design and develop engaging AI behaviors using behavior trees and navigation systems

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最近已更新!

March 2026

作业

15 项作业

授课语言:英语(English)

了解顶级公司的员工如何掌握热门技能

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

该课程共有15个模块

In this section, we introduce AI fundamentals in game development, focusing on agent movement, rule-based behaviors, and pathfinding algorithms for Unreal Engine applications.

涵盖的内容

2个视频2篇阅读材料1个作业

In this section, we explore Unreal Engine AI tools, focusing on Navigation System, Behavior Trees, Blackboards, Mass Entities, and Smart Objects for creating intelligent virtual agents.

涵盖的内容

1个视频2篇阅读材料1个作业

In this section, we explore the Unreal Engine Navigation System, focusing on AI movement, pathfinding algorithms, and testing with project templates to enhance realistic AI behavior in virtual environments.

涵盖的内容

1个视频3篇阅读材料1个作业

In this section, we explore setting up a navigation mesh in Unreal Engine, creating AI agents, and applying modifiers to enhance pathfinding in game environments.

涵盖的内容

1个视频4篇阅读材料1个作业

In this section, we explore dynamic navigation mesh generation, query filters for movement influence, and agent avoidance techniques to enhance AI behavior in Unreal Engine.

涵盖的内容

1个视频4篇阅读材料1个作业

In this section, we explore nav mesh optimization techniques, analyze resolution for performance, and debug navigation system issues to enhance AI agent movement efficiency.

涵盖的内容

1个视频2篇阅读材料1个作业

In this section, we explore behavior trees and Blackboards for AI decision-making in Unreal Engine, focusing on node types, execution order, and state management to create dynamic game experiences.

涵盖的内容

1个视频2篇阅读材料1个作业

In this section, we explore behavior tree implementation in Unreal Engine, focusing on tasks, services, and blackboards to create dynamic AI decision-making for game agents.

涵盖的内容

1个视频8篇阅读材料1个作业

In this section, we explore extending behavior trees in Unreal Engine by implementing custom tasks, designing efficient decorators, and debugging AI logic for improved character responsiveness and maintainability.

涵盖的内容

1个视频9篇阅读材料1个作业

In this section, we explore the Unreal Engine Perception System, focusing on implementing AI perception components, configuring stimuli, and debugging to enhance agent behavior and realism.

涵盖的内容

1个视频5篇阅读材料1个作业

In this section, we explore the Environment Query System (EQS) in Unreal Engine, focusing on setting up queries, integrating them into behavior trees, and enabling AI agents to make environment-aware decisions.

涵盖的内容

1个视频3篇阅读材料1个作业

In this section, we explore using state trees in Unreal Engine to design adaptive AI behaviors, focusing on structured decision-making and integration with game systems.

涵盖的内容

1个视频7篇阅读材料1个作业

In this section, we explore the Mass framework for efficient object management in Unreal Engine. Key concepts include configuring MassEntityConfigAsset and designing spawn blueprints for scalable AI systems.

涵盖的内容

1个视频4篇阅读材料1个作业

In this section, we explore Smart Objects in Unreal Engine to create interactive AI and player environments. Key concepts include defining Smart Object logic, using environment queries, and enhancing immersion through context-aware behavior.

涵盖的内容

1个视频3篇阅读材料1个作业

In this section, we explore C++ implementation in Unreal Engine, covering classes, delegates, interfaces, and garbage collection mechanisms for practical game development.

涵盖的内容

1个视频3篇阅读材料1个作业

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