Udemy

Ultimate Game AI for Godot Beginners

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  • 733 Students
  • Updated 3/2023
  • Certificate Available
4.4
(59 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
4 Hour(s) 4 Minute(s)
Language
English
Taught by
Adrian / Redefine Gamedev
Certificate
  • Available
  • *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
4.4
(59 Ratings)

Course Overview

Ultimate Game AI for Godot Beginners

Your Own Game AI. From 0 to Hero

By the end of this course you will implement your own AI System.


Find out the key components of a professional Game AI: Decision Making, Pathfinding and Compete & Collaborate.


Decision Making

Realtime decision making is one of the key components when creating a solid Game AI.

There are many ways to achieve this, be it either Finite State Machines, Behavior Trees, Planning.

The course focuses on Hierarchical Finite State Machines, an improvement over the original State Machines.

HFSM are currently used in modern games like Doom 2016. They are easy to understand and powerful.

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Learn how a Finite State Machine works and how to use a Hierarchical State Machine for your own game project.


Pathfinding

Once a decision is made, the AI Agent needs to move from A to B. Here is where pathfinding comes into play.

In these days, the pathfinding component is integrated in the game engine itself.

In the hands-on project we will make use of Godot's Navmesh System.

This course also focuses on teaching the core concepts of how a pathfinder works.

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Learn how a pathfinder works and how to create one from 0.

Find out how to use Godot's Navmesh in a Game AI project.

Discover how to create cover points and use them accordingly when picking a final destination.


Compete & Collaborate

The last piece of the puzzle of a great AI is also in this course!

Having the AI Agents not only detect what's around them by using sensors but also communicate between is a must in modern games.

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Learn how to implement range, field of view, raycast, hit detection and communication.


Find out how to give unique personalities to your AI Agents for a superior game experience


AI Personality: Aggressive

Meet the Agressive AI! Made to seek & kill with a low chance of retreat, this is the perfect killing machine!

It's main features are a linear projectile, a range sensor combined with raycast and a low chance of retreat.

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Learn how to put together an AI Agent that seeks to kill.


AI Personality: Defensive

Combining attacking with defense is another way to approach a fight. And this is how this AI operates.

Its main features are rocket projectiles, range/raycast sensors and a 50-50% attack/retreat chance.

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Learn how to put together a balanced AI Agent that not only seeks the target but also the nearest good cover.


AI Personality: Tactical

This AI never attacks directly. By having a long range sensor and no raycast, once the enemy is detected a vantage point will be also determined.

The Tactical AI goes to cover, adjusts for missed hits and fires a long-range projectile.

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Learn how to put together an AI Agent that uses long-range projectiles, adjusts for errors.


Full Game AI Project Included

You will get not only the examples, but also a full project that features an AI System ready to be used in a game - yes, yours included!

What you will be getting:

  • Relevant examples for each implementation part

  • Full modular project that you can explore and reuse for your game

  • Hierarchical Finite State Machines are used to implement the AI logic

  • Documented Source Code files in C#

  • 3 Types of AIs: Aggressive, Defensive and Tactical

  • 3 Projectile Types: Shell, Rocket and Mortar

  • 2 Types of Firing mode: Normal and Burst

  • 2 Patrol modes: Waypoints, Random Movement (interchangeable at runtime)

  • AI Communication System - propagate information between agents

  • Full Player Movement and Firing System

  • Game Assets - Buildings, Tanks and props

  • Everything properly organized in a tidy file structure, prefabs, modular components and more


Course Content

  • 8 section(s)
  • 39 lecture(s)
  • Section 1 Game AI - Introduction
  • Section 2 Understanding the Environment
  • Section 3 Finite State Machines
  • Section 4 From A to B - Pathfinding!
  • Section 5 Sensors
  • Section 6 Downloadables
  • Section 7 Full Game AI Project. Explained
  • Section 8 Extra

What You’ll Learn

  • What is a Game AI and how can it improve your game
  • What are the main components of a Game AI
  • How to implement different Game AI Systems
  • How to put everything together in a Game Project

Skills covered in this course


Reviews

  • L
    Lucas Silva
    3.5

    The course if good, but very outdated. Good for Godot 3.5.x, but if you are using Godot 4, there are a lot of features that could be handled better.

  • J
    Jose M Maisog
    5.0

    Very good match for me, at my "intermediate" level.

  • D
    D X
    4.5

    Good to learn about the different types of ai in games and in the real world.

  • T
    Troy Pepito
    5.0

    I found this course by searching for a solution to a physics formula problem that I had struggled to implement, which is the projectile with an arc. And thank goodness this course actually exists! I learned a lot of new methods and ways to streamline the workflow upon coding a unit or class. And much more useful stuff that I can integrate into my game projects!

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