Advanced AI For Games with Goal-Oriented Action Planning
Advanced AI For Games with Goal-Oriented Action Planning
Artificial Intelligence for Creating Complex Game Character Behaviours for Simulations, Real-Time Strategy Games & More
Product Brand: Udemy
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Udemy Coupon Code for Advanced AI For Games with Goal-Oriented Action Planning Course. Artificial Intelligence for Creating Complex Game Character Behaviours for Simulations, Real-Time Strategy Games & More
Created by Penny de Byl and Penny Holistic3D | 8 hours on-demand video course | 33 downloadable resources
Goal-Oriented Action Planning Course Overview
Throughout the course, you will follow along while a GOAP library and API are constructed from the ground up, to allow you intimate knowledge of the codebase. Alongside this, a simple hospital simulation will be constructed to test out the functionality of the library as it is put together. The simulation will also rely on Unity’s NavMesh System for navigation and path planning.
The course begins with an overview of Unity’s NavMesh System and covers the basic functionality needed for the hospital simulation. It then goes on to cover the concept of GOAP, where students will discover how goals, actions and plans interact. A planner will be constructed that dynamically builds each character’s sequence of actions, based on what they believe their goals are while in the simulation.
Following this, inventories will be introduced and developed to hold resources for individual characters. The resources in the inventories will be required for plan completion and also assist in directing a character’s navigation around the environment. This will then build to the design of more complex behaviours in which two characters must collaborate to complete a plan.
As the course continues, more characters with differing roles will be added and dynamically created and resources will be added and removed to develop a complex simulation. By the end of the course, students will have a hospital simulation with patients, nurses, doctors and janitors each with their own roles, goals, actions and required resources.
Although this course is not about building a completed game, a final section will provide some further knowledge on Unity development and examine methods for interacting with the environment such as: dragging and dropping items, dynamic NavMesh baking, user interface creation and camera movement to provide students with some direction on how such a simulation could be turned into a game.
At the completion of this course, students will have a fully-fledged GOAP library and API that they can reuse in their own game projects to provide game characters with complex intelligent behaviours.
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What you’ll 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.
Who this course is for:
- Anyone interested in learning how to better program their own non-player characters (NPCs) for believable behaviour.
- Anyone wanting to learn the advanced AI technique of GOAP to control their sims.
- Anyone interested in seeing how artificial intelligence is applied in computer games.
