Ultimate Game AI for Godot Beginners

Course Provided by:Adrian / Redefine Gamedev
Course Taken on: Udemy
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Description

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


Requrirements

Basic understanding of the Godot Engine. Lightweight or no programming skills.

Course Includes

  • 4 hours on-demand video
  • 27 downloadable resources
  • Access on mobile and TV
  • Full lifetime access
  • Certificate of completion

Course Reviews

  1. 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!
  2. I am an intermediate level programmer with a fundamental knowledge of Gdot4, gdscript and python/pygame. I completed Sections 1, 2 and 8 in that order as suggested by the author. These sections were pretty straight forward with no issues. Then I started Section 3: Finite State Machines (FSM). After opening up the code in Godot, there were several errors such as "Spatial class not defined". I checked thru the code and found several other errors which appears to be based on older versions of Godot which I was unable to resolve. Besides that, there is way too much going on in the provided FSM code that has not been covered. It felt like I arrived in the middle of the instruction rather than the beginning of this section. Will see how it goes as I get deeper, but this looks like its gonna have to be a refund. Too bad, as I felt this would go well with my "Introduction to AI" course that I am taking at the university as many of the algorithms we discuss in our class are at least discussed in the beginning sections of this course.
  3. Si imparano tecniche fondamentali di game prgramming, ottimo il materiale in pdf e ben spiegato. Consiglio questo corso a chiunque voglia migliorare drasticamente nello sviluppo di videogiochi.
  4. Bisogna avere acquisito delle basi di programmazione prima di approciarsi a questo corso.
  5. I gotta say I'm pretty impressed by the logics provided. I'm confident I will learn about how A.I. is made. And not just a walk through of code. I came here to learn how AI travels and all signs point in the right direction or should I say Z direction?