Implementing Movement and Decision-Making Systems

Coursera Courses ↗ · Coursera

Open Course on Coursera

Free to audit · Opens on Coursera

Implementing Movement and Decision-Making Systems

Coursera · Intermediate ·🤖 AI Agents & Automation ·1mo ago
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. Dive into the world of AI-driven vehicles and intelligent movement systems with this hands-on course. You will learn to program complex AI behaviors such as autonomous navigation, decision-making, and vehicle physics. The course covers topics like wheel physics, navigation meshes, finite state machines (FSMs), and autonomous movement patterns, empowering you to create dynamic, interactive agents that respond to their environment. The journey begins with vehicle physics, where you'll configure wheel colliders, apply forces, and set up a circuit with waypoints. Next, you’ll explore navigation meshes in Unity, optimizing AI movement through NavMesh agents and teaching characters how to follow and interact with players. The course also introduces the concept of finite state machines to structure your AI agents’ decision-making process, from patrolling to chasing and evading. This course is tailored for game developers looking to enhance their AI systems with advanced movement and decision-making capabilities. While it is ideal for intermediate learners, prior experience with Unity and basic programming concepts is recommended. By the end, you will have a deep understanding of how to implement autonomous agents in game environments and refine their behaviors for enhanced realism.
Watch on Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related AI Lessons

What if an AI continued thinking even after you closed the chat?
Explore the concept of AI systems that continue thinking after a conversation ends and its implications
Dev.to · Stell
UI/UX is for humans. DX is for developers. AX is for AI agents – and we just built it.
Learn about the concept of AX (Agent Experience) and its importance in designing APIs for AI agents, and how to build and secure APIs for AI interactions
Dev.to · anhmtk
Agent cost bugs are debugging bugs
Agent cost bugs can be caused by unexplainable runs, not just high bills, and require a different approach to debugging
Dev.to AI
Agent Boosting: The Missing Workflow for Getting Real Results from AI Coding Agents
Learn how to bridge the gap between AI coding agents' theoretical capabilities and practical results with Agent Boosting
Dev.to AI
Up next
Paperclip + Hermes Agent Is INSANE!
Julian Goldie SEO
Watch →