Forum Rockoldies
The Beginner'S Guide To Artificial Intelligence (Unity 2022) - Druckversion

+- Forum Rockoldies (https://rockoldies.net/forum)
+-- Forum: Fotobearbeitung - Photoshop (https://rockoldies.net/forum/forumdisplay.php?fid=16)
+--- Forum: E-Learning, Tutorials (https://rockoldies.net/forum/forumdisplay.php?fid=18)
+--- Thema: The Beginner'S Guide To Artificial Intelligence (Unity 2022) (/showthread.php?tid=68537)

The Beginner'S Guide To Artificial Intelligence (Unity 2022) - Panter - 03.03.2023

[Bild: qmyw87vw858f52v4xajexord9f.jpg]

The Beginner'S Guide To Artificial Intelligence (Unity 2022)
Last updated 8/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 20.48 GB | Duration: 30h 11m

A practical guide to programming non-player characters for games in the Unity Game Engine with C#



What you'll learn
Design and program NPCs with C# in Unity
Explain how AI is applied in computer games
Implement AI-related Unity Asset plugins into existing projects
Work with a variety of AI techniques for developing navigation and decision making abilities in NPCs

Requirements
You should be familiar with C# and the Unity Game Development Engine.

Description
Do your non-player characters (NPCs) lack drive and ambition? Are they slow, stupid and constantly banging their heads against the wall? Then this course is for you. Join Penny as she explains, demonstrates and assists you in creating your very own NPCs in Unity with C#. All you need is a sound knowledge of Unity, C# and the ability to add two numbers together.This course uses Unity Version 2021.3 LTSIn this course, Penny reveals the most popular AI techniques used for creating believable character behaviour in games using her internationally acclaimed teaching style and knowledge from over 30 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 teach you about the fundamental AI techniques used in today's games. You'll join in as NPCs are programmed to chase, patrol, shoot, race, crowd and much more.Learn how to program and work with:vectorswaypointsnavmeshesthe A* algorithmcrowdsflocksanimated charactersvehiclesand industry standard techniques such as goal-oriented action learning and behaviour trees.Contents and OverviewThe course begins with a detailed examination of vector mathematics that sits at the very heart of programming the movement of NPCs. Following this, systems of waypoints will be used to move characters around in an environment before examining the Unity waypoint system for car racing with AI controlled cars. This leads into an investigation of graph theory and the A* algorithm before we apply these principles to developing navmeshes and developing NPCs who can find their way around a game environment. Before an aquarium is programmed complete with autonomous schooling fish, crowds of people will be examined from the recreation of sidewalk traffic, to groups of people fleeing from danger. Having examined the differing ways to move NPCs around in a game environment, their thinking abilities will be discussed with full explanations and more hands-on workshops using finite state machines and behaviour trees.The follow-along workshops included in the course come with starter Unity asset files and projects complete with solutions. Throughout, there are also quizzes and challenge exercises to reinforce your learning and guide you to express your newfound knowledge.At the completion of this course you will have gained a broad understanding of what AI is in games, how it works and how you can use it in your own projects. It will equip you with a toolset to examine any of the techniques presented in more depth to take your game environments to the next level.What students are saying about this course:This has been my favourite Udemy-Unity course so far. It took me from literally 0% knowledge of how game AI is achieved, and took me to a whole new level. Waypoints, pathfinding, state machines, etc etc etc are all covered in-depth and will reveal the magic (spoiler alert: it isn't magic) behind making your computer characters seem like they really have a mind of their own.Oh My God. I love her way of teaching things. I haven't finished this course yet. But all i can say is that it is another brilliant course from her. Artificial intelligence by itself is a tricky thing to do. And before starting this course i never thought that i will understand anything in it. But i was wrong. With her style of teaching, you will learn how to move your characters in an "intelligent" way. This course is perfectly sliced and the pace is wonderful.

Overview

Section 1: Introduction

Lecture 1 Welcome to the Course

Lecture 2 Introduction to Artificial Intelligence

Lecture 3 Join the H3D Student Community

Lecture 4 FAQs

Lecture 5 Not So Scary Vector Mathematics

Lecture 6 Vector Mathematics Basics Cheat Sheet

Section 2: The Mathematics of AI

Lecture 7 The Cartesian plane

Lecture 8 Vectors Part 1

Lecture 9 Vectors Part 2

Lecture 10 Vectors Part 3

Lecture 11 Calculating Distance Part 1

Lecture 12 Calculating Distance Part 2

Lecture 13 Calculating the Dot Product

Lecture 14 Calculating the Angle Between Vectors

Lecture 15 Calculating the Cross Project

Lecture 16 A Simple Autopilot Project

Lecture 17 A Simple AI Pet Challenge Project

Section 3: The Physics of AI

Lecture 18 Time

Lecture 19 Normalising Movement with Time

Lecture 20 Velocity

Lecture 21 Predicting Future Locations of Game Objects Part 1

Lecture 22 Predicting Future Locations of Game Objects Part 2

Lecture 23 Acceleration Part 1

Lecture 24 Acceleration Part 2

Lecture 25 Acceleration Part 3

Lecture 26 Trajectories Part 1

Lecture 27 Trajectories Part 2

Lecture 28 Trajectories Part 3

Section 4: The A* Algorithm

Lecture 29 The A* Pathfinding Algorithm Part 1

Lecture 30 The A* Pathfinding Algorithm Part 2

Lecture 31 The A* Pathfinding Algorithm Part 3

Lecture 32 The A* Pathfinding Algorithm Part 4

Lecture 33 The A* Pathfinding Algorithm Part 5

Lecture 34 The A* Pathfinding Algorithm Part 6

Section 5: Waypoints and Graphs

Lecture 35 Waypoints

Lecture 36 Slerping to the Direction of Travel

Lecture 37 Following a Circuit

Lecture 38 Following a Tracker

Lecture 39 Using A* with Waypoints Part 1

Lecture 40 A Simple Graph API Part 1

Lecture 41 A Simple Graph API Part 2

Lecture 42 A Simple Graph API Part 3

Lecture 43 Using A* with Waypoints Part 2

Lecture 44 Traversing a Path

Lecture 45 Giving Commands to Pathfind

Section 6: Vehicles

Lecture 46 Setting up Wheel Physics

Lecture 47 Forces on Wheels

Lecture 48 Constructing a Simple Car

Lecture 49 Turning the Steering Wheel

Lecture 50 Creating A Circuit with Waypoints

Lecture 51 Automatically Driving a Circuit Part 1

Lecture 52 Braking

Lecture 53 Driving Forces

Lecture 54 Improved Driving Tactics

Lecture 55 Adding a Progress Tracker

Lecture 56 Adding Antiroll Stabilising

Lecture 57 Reconfiguring for Car Setting Testing

Lecture 58 Avoiding Other Drivers

Lecture 59 Improving Avoidance and Reversing

Section 7: Navigation Meshes

Lecture 60 Navigation Mesh Introduction

Lecture 61 From Waypoints to Navigation Meshes

Lecture 62 NavMesh Agents Part 1

Lecture 63 NavMesh Agents Part 2

Lecture 64 NavMesh Agents Part 3

Lecture 65 Following a Player on a NavMesh

Section 8: Finite State Machines

Lecture 66 Finite State Machines

Lecture 67 Creating a State Class

Lecture 68 Patrolling

Lecture 69 Building the AI Class

Lecture 70 Chasing the Player Part 1

Lecture 71 Chasing the Player Part 2

Lecture 72 FSM Challenge

Section 9: Autonomously Moving Agents

Lecture 73 Seek and Flee

Lecture 74 Pursuit

Lecture 75 Evade

Lecture 76 Wander

Lecture 77 Hide Part 1

Lecture 78 Hide Part 2

Lecture 79 Hide Part 3

Lecture 80 Complex Behaviours

Lecture 81 Behaviour Challenge

Section 10: Crowd Simulation

Lecture 82 Moving As One

Lecture 83 Creating a City Crowd Part 1

Lecture 84 Creating a City Crowd Part 2

Lecture 85 Fleeing Part 1

Lecture 86 Fleeing Part 2

Lecture 87 Flocking Part 1

Lecture 88 Flocking Part 2

Lecture 89 Flocking Part 3

Lecture 90 Flocking Part 4

Lecture 91 Crowd Challenge Project

Lecture 92 Flock Challenge Project

Section 11: Goal Driven Behaviour

Lecture 93 An Introduction to GOAP

Lecture 94 Setting up a GOAP Environment

Lecture 95 Preplanning the agent's actions

Lecture 96 The World States

Lecture 97 Actions

Lecture 98 Agents

Lecture 99 The GOAP Planner Part 1

Lecture 100 The GOAP Planner Part 2

Lecture 101 Executing a Simple Plan

Lecture 102 Creating a Multistep Plan

Lecture 103 Spawning Patients

Lecture 104 Plans that Require Multiple Agents

Lecture 105 Matching Agents with Agents

Lecture 106 Adding More Resources to the World

Lecture 107 Implementing the Inventory System

Lecture 108 Moving the Nurse

Lecture 109 Adding a Goal Challenge

Section 12: Behaviour Trees

Lecture 110 Introducing Behaviour Trees

Lecture 111 Nodes

Lecture 112 Tree Printing

Lecture 113 Leaf and Action Nodes

Lecture 114 NavMesh Movement

Lecture 115 Sequences

Lecture 116 Selectors

Lecture 117 Extended Action Methods

Lecture 118 Conditions

Section 13: Final Words

Lecture 119 Some Final Words from Penny

Lecture 120 Where to now?

Section 14: Moving

Lecture 121 This is the previous version of the course.

Lecture 122 Vectors and Moving in a Straight Line

Lecture 123 Traveling to a Goal Location

Lecture 124 Pushing the Character Forward

Lecture 125 Slerping

Lecture 126 About Animation and Translation

Lecture 127 Waypoints

Lecture 128 Challenge

Section 15: Cars

Lecture 129 Unity's Waypoint System

Lecture 130 Car Racing with Waypoints

Lecture 131 Customising Car Behaviours

Lecture 132 Unity's Vehicle System

Section 16: Waypoints

Lecture 133 Graph Theory and Pathfinding

Lecture 134 Pathfinding through Waypoints

Lecture 135 Pathfinding through Waypoints Part 2

Lecture 136 Challenge

Lecture 137 Waypoints in 2D

Section 17: NavMeshes

Lecture 138 NavMesh Basics

Lecture 139 From Waypoints to NavMesh

Lecture 140 NavMesh Agents Part 1

Lecture 141 NavMesh Agents Part 2

Lecture 142 Following a Player on A NavMesh and Setting-Up Off Mesh Links

Lecture 143 Fixing Mixamo Textures

Lecture 144 Animating on a NavMesh

Lecture 145 Syncing Animation Speed with NavMesh Agent Speed

Lecture 146 Multiple NavMeshes for Different Agent Sizes

Lecture 147 Challenge

Section 18: Autonomously Moving Agents

Lecture 148 Seek and Flee

Lecture 149 Pursuit

Lecture 150 Evade

Lecture 151 Wander

Lecture 152 Hide Part 1

Lecture 153 Hide Part 2

Lecture 154 Complex Behaviours

Lecture 155 Behaviour Challenge

Section 19: Moving As One

Lecture 156 Crowd Simulation

Lecture 157 Creating a City Crowd Part 1

Lecture 158 Creating a City Crowd Part 2

Lecture 159 Fleeing

Lecture 160 Flocking Part 1

Lecture 161 Flocking Part 2

Lecture 162 Flocking Part 3

Lecture 163 Challenge 1

Lecture 164 Challenge 2

Lecture 165 Challenge 3

Section 20: Let's Start Thinking

Lecture 166 Line of Sight

Lecture 167 Finite State Machines Part 1

Lecture 168 Finite State Machines Part 2

Lecture 169 Finite State Machines Part 3

Lecture 170 Converting the FSM to Work on a Navmesh

Lecture 171 Challenge

Section 21: Behaviour Trees

Lecture 172 Introduction to Behaviour Trees

Lecture 173 Sequence Nodes Part 1

Lecture 174 Sequence Nodes Part 2

Lecture 175 Embedding Logic in Behaviour Trees

Lecture 176 Selector Nodes

Lecture 177 More Logic for Complex Behaviours

Lecture 178 Putting Together a Complex Behaviour Tree

Lecture 179 Challenge

Section 22: Goal-Orientated Action Planning

Lecture 180 Introduction to GOAP

Lecture 181 Getting Started with GOAP in Unity

Lecture 182 Adding Actions to GOAP

Lecture 183 Adding Multiple Plans to GOAP

Lecture 184 Global States and Multiple Agents

Section 23: End Words

Lecture 185 Where To Now?

Anyone interested in learning how to program their own non-player characters (NPCs).,Anyone interested in seeing how artificial intelligence is applied in computer games.

Homepage
Show Content

[Bild: 84creatingacitycrowdpdleis.jpg]

Show Content
Show Content
Show Content