Goal-Oriented Action Planning - Advanced AI For Games

Why take this course?
🎓 Advanced AI For Games with Goal-Oriented Action Planning - Course by Penny de Byl 🚀
Headline: Dive into the World of Advanced AI for Game Character Behaviours! 🤖
Course Title: Advanced AI For Games with Goal-Oriented Action Planning
Course Description:
Welcome to the fascinating journey of Artificial Intelligence in games, specifically tailored for creating complex and believable game character behaviours in simulations, real-time strategy games, and beyond! 🎮✨
Goal-Oriented Action Planning (GOAP) is an AI architecture that breathes life into game characters, enabling them to set goals and plan actions based on their environment and resources. Unlike traditional methods, GOAP is efficient, versatile, and can be applied across various genres without the need for cumbersome finite state machines. 🧠
In this comprehensive course, Penny de Byl demystifies GOAP using her renowned international teaching style and decades of experience in games, graphics, and AI—as seen in her award-winning books. You'll engage in hands-on workshops where you'll build the entire GOAP library from scratch while developing a hospital simulation scenario to test your API on the fly. 🏥➡️✅
Key Learning Points:
- GOAP Library & API: Learn to program and implement a reusable GOAP library that can be adapted for a multitude of game projects.
- Goals, Actions, States, & Beliefs: Understand how these elements define the game environment and character decision-making processes.
- Navigation Meshes & Agents: Master advanced path planning and navigation capabilities for characters within your game world.
- Dynamic Building of NavMeshes: Discover how to reposition resources in the environment dynamically for optimal performance.
- Inventories: Implement inventories to manage resources that are essential for character goals and tasks.
- Unity UI System: Learn to manipulate draggable resources within a game environment using Unity's UI system.
Course Contents & Overview:
- NavMesh System Overview in Unity: Get acquainted with the basics of Unity's NavMesh System for your hospital simulation.
- Introduction to GOAP: Explore how goals, actions, and plans interact and construct a planner that dynamically builds character sequences of actions.
- Inventory Design & Development: Introduce and develop inventories for holding resources necessary for plan completion and character navigation.
- Complex Behaviours & Collaboration: Create scenarios where characters must work together to achieve their objectives.
- Advanced Character Roles & Resource Management: Add a variety of roles such as patients, nurses, doctors, and janitors with complex goals and required resources.
- Towards Game Development: Gain insights into interacting with the environment, including dynamic NavMesh baking, user interface creation, camera movement, and more.
By course's end, you will possess a fully-fledged GOAP library and API, ready to be utilized in your own game projects for intelligent, complex character behaviours. 🛠️🚀
Student Feedback:
- "Enrolling in this course was a game-changer for me. Finding the words to express my gratitude for Penny's teachings is the hardest part!" 🌟
- "Penny's teaching approach is holistic, and I've learned so much about coding effectively within just a few hours, thanks to her detailed explanations!" 📚✨
- "As an instructor, Penny is excellent. She has the unique ability to break down complex concepts into smaller, understandable topics." 🎓👍
Join us and transform your game characters from static entities to dynamic personalities that captivate and engage players like never before! 🏆🎉
Enroll Now & Elevate Your Game Development Skills with Goal-Oriented Action Planning! 📲🎫
Course Gallery




Loading charts...
Comidoc Review
Our Verdict
An engaging and informative course on GOAP algorithm in game development. Despite minor drawbacks such as confusing variable names and a few beginner-level topics, the course remains an invaluable resource for building your own GOAP system. The project provided demonstrates how to integrate the GOAP into your own games effectively. While comprehensive, some parts like GPlanner implementation could offer more detailed explanations and graphics.
What We Liked
- In-depth look at GOAP algorithm, providing a solid understanding of its implementation
- Covers dynamic and static resources, agents, world states, and individual states
- Clear explanations with insightful examples, enabling me to build my own GOAP system
- Provides a project showcasing the GOAP in action, offering valuable learning opportunities
- Award-winning and engaging teaching style, making it easy to follow advanced concepts
Potential Drawbacks
- Variable naming could be more descriptive for easier GOAP code comprehension
- Code refactoring section missing, leading to poorly written and optimized code
- Some beginner-level topics included, increasing the complexity in an advanced course
- Lacks detailed explanation of GPlanner implementation and individual class responsibilities