Practical guide to AI in Unity
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 48000 Hz, 2ch | Size: 3.83 GB
Genre: eLearning Video | Duration: 27 lectures (4 hour, 44 mins) | Language: English

Create a colony-simulation-game with State-Machines and Behavior-Trees

What you'll learn

    Lay the foundation for a Colony-Survival Game like Rimworld or Oxygen Not Included
    Develop simple and complex practical AI Solutions for your games
    Create a simple AI with State Machines
    Make extensible State Machines with the State Pattern
    Develop a complex AI with Behaviour Trees
    Master the Behavior Designer Plugin
    Simulate an ecology with Genetic Algorithms

Requirements

    Installed Unity v2019.3
    Basic understanding of Unity
    Basic understanding of C#

Description

Learn how to create state of the art AI for video games using Unity.

I believe in a practical approach in learning so this course will be primarily project-based. You won't just learn dry theory and forget everything within a matter of days but instead apply the learned concepts to two actual Unity-Projects:

    Catch: A simple digital replica of play every kid's favourite game: catch

    Colony Simulation: A game like Rimworld or Oxygen Not Included, where you can't control the NPCs directly, but instead they are controlled by the AI and you need to help them survive by making sure they've got enough to eat.

Also this course contains a free exclusive Behavior-Designer Educational-License, which would normally cost ~70$. Behavior Designer is the industry-standard solution for Behaviortrees and generously provided me with an exclusive Educational License, which they specifically built for this course. So you won't get it anywhere else.

Also you will of course get full lifetime access to the course.

We'll start with the simplest AI-System that there is, namely State-Machines.

After that we'll improve State-Machines and make them more extensible with the State-Pattern.

Then we'll hit the main topic which is one of the more advanced techniques that are used in Indie- and AAA-Gameproductions alike: BehaviorTrees.

Lastly we'll have a glimpse at one of the more experimental AI-Approaches, namely Genetic Algorithms, which are more of a niche topic but have the potential for very interesting game-mechanics that stand out of the crowd.

Whereas this course is already rather extensive and covers the most important aspects of AI for modern gamedevelopment, I can't possibly cover everything of this huge field. For example I won't address machine learning because this topic alone would fill a whole bunch of courses and really isn't that practical for most Game-AIs because of the lack of control you have over it.

By the end of the course you'll be confident with the most important AI-Techniques- and Design Patterns for modern Gamedevelopment.

So what are you waiting for, join me now and start creating astonishing AI-Systems yourself.

Who this course is for:

    Intermediate Gameprogrammers with an interest in AI in Unity
    Gamedesigners with some Coding- and Unity-Background
   

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