Advanced AI For Games with Goal-Oriented Action Planning

Advanced AI For Games with Goal-Oriented Action Planning, available at $84.99, has an average rating of 4.6, with 41 lectures, based on 613 reviews, and has 7255 subscribers.

You will learn about 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. This course is ideal for individuals who are Anyone interested in learning how to better program their own non-player characters (NPCs) for believable behaviour. or Anyone wanting to learn the advanced AI technique of GOAP to control their sims. or Anyone interested in seeing how artificial intelligence is applied in computer games. It is particularly useful for Anyone interested in learning how to better program their own non-player characters (NPCs) for believable behaviour. or Anyone wanting to learn the advanced AI technique of GOAP to control their sims. or Anyone interested in seeing how artificial intelligence is applied in computer games.

Enroll now: Advanced AI For Games with Goal-Oriented Action Planning

Summary

Title: Advanced AI For Games with Goal-Oriented Action Planning

Price: $84.99

Average Rating: 4.6

Number of Lectures: 41

Number of Published Lectures: 41

Number of Curriculum Items: 41

Number of Published Curriculum Objects: 41

Original Price: $19.99

Quality Status: approved

Status: Live

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.

Who Should Attend

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.

Target Audiences

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.

Goal-Oriented Action Planning (GOAP)is an AI architecture that provides game characters with the ability to select goals and make plans to achieve those goals based on the state of the environment and available resources.  It can be used across a wide range of game genres from first-person shooters to real-time strategies, to develop intelligent characters capable of making smart decisions without the need for large finite state machines.   The codebase is deceptively simple and yet logical, reusable and extremely powerful.  The library is written in C#and implemented in Unity V.2019,however will easily port to other applications.

In this course, Penny demystifies the advanced AI technique of GOAP used for creating believable and intelligent game characters in games using her internationally acclaimed teaching style and knowledge from over 25 years working with games, graphics and having written two award-winning books on games AI. Throughout, you will follow along with hands-on workshops designed to take you through every step of putting together your own GOAP API.  You will build the entire GOAP library from the ground up while building a hospital simulation scenario in parallel, to test the API as you go.

Learn how to program and work with:

A GOAP Library and API that’s reusable across a wide range of game projects.

Goals, Actions, States and Beliefs that define the state of the game environment, what individual characters want to do and how they understand their world.

Navigation Meshes and Agents that provide advanced path planning and navigation capabilities for characters.

Dynamic Building of NavMeshes to allow for the repositioning of resources in the environment.

Inventories for each character for use in completing tasks that satisfy character goals.

The Unity UI system to move draggable resources into a game environment.

Contents and 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.

What students are saying about Penny’s courses:

Turns out, the hardest part of this course for me is finding the words to describe how glad I am to have enrolled in it.

I honestly love Hollistic’s teaching approach and I’ve never learned so much within a few hours about coding effectively with such detailed explanations!

Penny is an excellent instructor and she does a great job of breaking down complex concepts into smaller, easy-to-understand topics.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Join the H3D Student Community

Lecture 3: Contacting H3D

Lecture 4: FAQs

Chapter 2: A Crash Course in Navigation Meshes

Lecture 1: An Introduction to Navigation Meshes

Lecture 2: Setting up your own NavMesh

Lecture 3: Moving an Agent Around the Mesh

Chapter 3: Introduction to GOAP

Lecture 1: GOAP Introduction

Lecture 2: Setting up a GOAP Environment

Lecture 3: Preplanning the Agent Actions

Lecture 4: The World States

Lecture 5: Actions

Lecture 6: Agents

Chapter 4: Planning

Lecture 1: The GOAP Planner Part 1

Lecture 2: The GOAP Planner Part 2

Lecture 3: Executing a Simple Plan

Lecture 4: Creating a Multistep Plan

Lecture 5: Plans that Require Multiple Agents

Chapter 5: Inventories

Lecture 1: Adding More Resources to the World

Lecture 2: Implementing an Inventory System

Chapter 6: Complex Behaviours

Lecture 1: Moving the Nurse

Lecture 2: Adding Goal Challenge

Lecture 3: Taking a Break

Chapter 7: Building Functionality and Debugging

Lecture 1: Adding a Doctor Challenge

Lecture 2: New Resource Models and Troubleshooting Part 1

Lecture 3: New Resource Models and Troubleshooting Part 2

Lecture 4: New Resource Challenge

Lecture 5: Reusing Actions on Other Agents

Chapter 8: Producing and Removing Resources

Lecture 1: A Little World Refactoring

Lecture 2: Monitoring Agent States

Lecture 3: Responding to a New Resource

Chapter 9: Interacting with the Environment

Lecture 1: Dragging and Dropping New Resources

Lecture 2: Dynamic Navmesh Baking

Lecture 3: Repositioning and Rotating Resources

Lecture 4: Deleting a Resource

Lecture 5: Refactoring for a Multi-resource UI

Lecture 6: A UI to Work with Multiple Resources

Lecture 7: Improved Repositioning

Lecture 8: Moving the Camera

Chapter 10: Final Words

Lecture 1: Some Final Words from Penny

Lecture 2: Where to now?

Instructors

Penny de Byl
International Award Winning Professor & Best Selling Author

Penny Holistic3D
Academic, Author & Game Development Enthusiast

Rating Distribution

1 stars: 3 votes

2 stars: 11 votes

3 stars: 40 votes

4 stars: 151 votes

5 stars: 408 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!