Goal-Oriented Action Planning - Advanced AI For Games
Artificial Intelligence for Creating Complex Game Character Behaviours for Simulations, Real-Time Strategy Games & More
4.68 (635 reviews)
7 588
students
8.5 hours
content
Feb 2025
last update
$74.99
regular price
What you will learn
How to design and program more intelligent behaving Non-Player Characters with C#.
How goals, states, actions, believes and path-planning can be applied in computer games.
The finer workings of a Goal-Oriented Action Planning (GOAP) library and building one from scratch.
How to develop and debug your own simulations.
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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
Related Topics
2740930
udemy ID
05/01/2020
course created date
12/01/2020
course indexed date
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