Unity artificial intelligence programming :: add powerful, believable, and fun AI entities in your game with the power of Unity 2018! /
Learn and Implement game AI in Unity 2018 to build smart game environments and enemies with A*, Finite State Machines, Behavior Trees and NavMesh. Key Features Build richer games by learning the essential concepts in AI for games like Behavior Trees and Navigation Meshes Implement character behavior...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK :
Packt Publishing,
2018.
|
| Ausgabe: | Fourth edition. |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Learn and Implement game AI in Unity 2018 to build smart game environments and enemies with A*, Finite State Machines, Behavior Trees and NavMesh. Key Features Build richer games by learning the essential concepts in AI for games like Behavior Trees and Navigation Meshes Implement character behaviors and simulations using the Unity Machine Learning toolkit Explore the latest Unity 2018 features to make implementation of AI in your game easier Book Description Developing Artificial Intelligence (AI) for game characters in Unity 2018 has never been easier. Unity provides game and app developers with a variety of tools to implement AI, from the basic techniques to cutting-edge machine learning-powered agents. Leveraging these tools via Unity's API or built-in features allows limitless possibilities when it comes to creating your game's worlds and characters. This fourth edition with Unity will help you break down AI into simple concepts to give you a fundamental understanding of the topic to build upon. Using a variety of examples, the book then takes those concepts and walks you through actual implementations designed to highlight key concepts and features related to game AI in Unity. Further on, you'll learn how to distinguish the state machine pattern and implement one of your own. This is followed by learning how to implement a basic sensory system for your AI agent and coupling it with a Finite State Machine (FSM). Next, you'll learn how to use Unity's built-in NavMesh feature and implement your own A* pathfinding system. You'll then learn how to implement simple ?ocks and crowd dynamics, which are key AI concepts in Unity. Moving on, you'll learn how to implement a behavior tree through a game-focused example. Lastly, you'll apply all the concepts in the book to build a popular game. What you will learn Create smarter game worlds and characters with C# programming Apply automated character movement using pathfinding and steering behaviors Implement non-player character decision-making algorithms using Behavior Trees and FSMs Build believable and highly efficient artificial flocks and crowds Create sensory systems for your AI with the most commonly used techniques Construct decision-making systems to make agents take different actions Explore the application of machine learning in Unity Who this book is for This book is intended for Unity developers with a basic understanding of C# and the Unity editor. Whether you're looking to build your f... |
| Beschreibung: | 1 online resource (1 volume) : illustrations |
| Bibliographie: | Includes bibliographical references. |
| ISBN: | 1789531454 9781789531459 |
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| 245 | 1 | 0 | |a Unity artificial intelligence programming : |b add powerful, believable, and fun AI entities in your game with the power of Unity 2018! / |c Dr. Davide Aversa, Aung Sithu Kyaw, Clifford Peters. |
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| 505 | 0 | |a To get the most out of this book -- Get in touch -- Introduction to AI -- Artificial Intelligence (AI) -- AI in games -- AI techniques -- Summary -- Finite State Machines -- The player's tank -- Initialization -- Shooting bullet -- Controlling the tank -- The Bullet class -- Setting up waypoints -- The abstract FSM class -- The enemy tank AI -- The Patrol state -- The Chase state -- The Attack state -- The Dead state -- Taking damage -- Using an FSM framework -- The AdvanceFSM class -- The FSMState class -- The state classes -- The PatrolState class -- The NPCTankController class -- Summary -- Randomness and Probability -- Randomness in games -- Definitions of probability -- Character personalities -- FSM with probability -- Dynamic AI -- Demo slot machine -- Summary -- Further reading -- Implementing Sensors -- Basic sensory systems -- Scene setup -- The player's tank and the aspect class -- AI characters -- Testing -- Summary -- Flocking -- Basic flocking behavior -- Individual behavior -- Controller -- Alternative implementation -- FlockController -- Summary -- Path-Following and Steering Behaviors -- Following a path -- Path script -- Path-following agents -- Avoiding obstacles -- Adding a custom layer -- Obstacle avoidance -- Summary -- A* Pathfinding -- Revisiting the A* algorithm -- Implementing the A* algorithm -- Node -- PriorityQueue -- The GridManager class -- The AStar class -- The TestCode class -- Setting up the scene -- Testing the pathfinder -- Summary -- Navigation Mesh -- Setting up the map -- Navigation static -- Baking the navigation mesh -- NavMesh agent -- Updating an agents' destinations -- Scene with slope -- Navigation areas -- Off Mesh Links -- Generated Off Mesh Links -- Manual Off Mesh Links -- Summary -- Behavior Trees -- Introduction to Behavior Trees -- A simple example - patrolling robot -- Implementing a BT in Unity with Behavior Bricks -- Set up the scene -- Implement a Day/Night cycle -- Design the Enemy Behavior -- Implement the Nodes -- Building the Tree -- Attach the BT to the Enemy -- Summary -- External Resources -- Machine Learning in Unity -- The Unity Machine Learning Agents Toolkit -- How to install the ML-Agents Toolkit -- Installing Python and TensorFlow on Windows -- Installing Python and TensorFlow on macOS and Unix-like systems -- Using the ML-Agents Toolkit - a basic example -- Creating the scene -- Implementing the code -- Adding the final touches -- Training a Brain object -- Training the agent -- Summary -- Further reading -- Putting It All Together -- Basic game structure -- Adding automated navigation -- Creating the NavMesh -- Setting up the agent -- Fixing the GameManager script -- Creating decision-makingAI with FSM -- Summary. | |
| 520 | |a Learn and Implement game AI in Unity 2018 to build smart game environments and enemies with A*, Finite State Machines, Behavior Trees and NavMesh. Key Features Build richer games by learning the essential concepts in AI for games like Behavior Trees and Navigation Meshes Implement character behaviors and simulations using the Unity Machine Learning toolkit Explore the latest Unity 2018 features to make implementation of AI in your game easier Book Description Developing Artificial Intelligence (AI) for game characters in Unity 2018 has never been easier. Unity provides game and app developers with a variety of tools to implement AI, from the basic techniques to cutting-edge machine learning-powered agents. Leveraging these tools via Unity's API or built-in features allows limitless possibilities when it comes to creating your game's worlds and characters. This fourth edition with Unity will help you break down AI into simple concepts to give you a fundamental understanding of the topic to build upon. Using a variety of examples, the book then takes those concepts and walks you through actual implementations designed to highlight key concepts and features related to game AI in Unity. Further on, you'll learn how to distinguish the state machine pattern and implement one of your own. This is followed by learning how to implement a basic sensory system for your AI agent and coupling it with a Finite State Machine (FSM). Next, you'll learn how to use Unity's built-in NavMesh feature and implement your own A* pathfinding system. You'll then learn how to implement simple ?ocks and crowd dynamics, which are key AI concepts in Unity. Moving on, you'll learn how to implement a behavior tree through a game-focused example. Lastly, you'll apply all the concepts in the book to build a popular game. What you will learn Create smarter game worlds and characters with C# programming Apply automated character movement using pathfinding and steering behaviors Implement non-player character decision-making algorithms using Behavior Trees and FSMs Build believable and highly efficient artificial flocks and crowds Create sensory systems for your AI with the most commonly used techniques Construct decision-making systems to make agents take different actions Explore the application of machine learning in Unity Who this book is for This book is intended for Unity developers with a basic understanding of C# and the Unity editor. Whether you're looking to build your f... | ||
| 630 | 0 | 0 | |a Unity (Electronic resource) |0 http://id.loc.gov/authorities/names/n2011038776 |
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| 650 | 0 | |a Artificial intelligence. |0 http://id.loc.gov/authorities/subjects/sh85008180 | |
| 650 | 0 | |a Three-dimensional display systems. |0 http://id.loc.gov/authorities/subjects/sh85135021 | |
| 650 | 2 | |a Artificial Intelligence |0 https://id.nlm.nih.gov/mesh/D001185 | |
| 650 | 6 | |a Jeux vidéo |x Programmation. | |
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| contents | To get the most out of this book -- Get in touch -- Introduction to AI -- Artificial Intelligence (AI) -- AI in games -- AI techniques -- Summary -- Finite State Machines -- The player's tank -- Initialization -- Shooting bullet -- Controlling the tank -- The Bullet class -- Setting up waypoints -- The abstract FSM class -- The enemy tank AI -- The Patrol state -- The Chase state -- The Attack state -- The Dead state -- Taking damage -- Using an FSM framework -- The AdvanceFSM class -- The FSMState class -- The state classes -- The PatrolState class -- The NPCTankController class -- Summary -- Randomness and Probability -- Randomness in games -- Definitions of probability -- Character personalities -- FSM with probability -- Dynamic AI -- Demo slot machine -- Summary -- Further reading -- Implementing Sensors -- Basic sensory systems -- Scene setup -- The player's tank and the aspect class -- AI characters -- Testing -- Summary -- Flocking -- Basic flocking behavior -- Individual behavior -- Controller -- Alternative implementation -- FlockController -- Summary -- Path-Following and Steering Behaviors -- Following a path -- Path script -- Path-following agents -- Avoiding obstacles -- Adding a custom layer -- Obstacle avoidance -- Summary -- A* Pathfinding -- Revisiting the A* algorithm -- Implementing the A* algorithm -- Node -- PriorityQueue -- The GridManager class -- The AStar class -- The TestCode class -- Setting up the scene -- Testing the pathfinder -- Summary -- Navigation Mesh -- Setting up the map -- Navigation static -- Baking the navigation mesh -- NavMesh agent -- Updating an agents' destinations -- Scene with slope -- Navigation areas -- Off Mesh Links -- Generated Off Mesh Links -- Manual Off Mesh Links -- Summary -- Behavior Trees -- Introduction to Behavior Trees -- A simple example - patrolling robot -- Implementing a BT in Unity with Behavior Bricks -- Set up the scene -- Implement a Day/Night cycle -- Design the Enemy Behavior -- Implement the Nodes -- Building the Tree -- Attach the BT to the Enemy -- Summary -- External Resources -- Machine Learning in Unity -- The Unity Machine Learning Agents Toolkit -- How to install the ML-Agents Toolkit -- Installing Python and TensorFlow on Windows -- Installing Python and TensorFlow on macOS and Unix-like systems -- Using the ML-Agents Toolkit - a basic example -- Creating the scene -- Implementing the code -- Adding the final touches -- Training a Brain object -- Training the agent -- Summary -- Further reading -- Putting It All Together -- Basic game structure -- Adding automated navigation -- Creating the NavMesh -- Setting up the agent -- Fixing the GameManager script -- Creating decision-makingAI with FSM -- Summary. |
| ctrlnum | (OCoLC)1084292723 |
| dewey-full | 794.81526 |
| dewey-hundreds | 700 - The arts |
| dewey-ones | 794 - Indoor games of skill |
| dewey-raw | 794.81526 |
| dewey-search | 794.81526 |
| dewey-sort | 3794.81526 |
| dewey-tens | 790 - Recreational and performing arts |
| discipline | Sport |
| edition | Fourth edition. |
| format | Electronic eBook |
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| id | ZDB-4-EBA-on1084292723 |
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| indexdate | 2024-11-27T13:29:20Z |
| institution | BVB |
| isbn | 1789531454 9781789531459 |
| language | English |
| oclc_num | 1084292723 |
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| record_format | marc |
| spelling | Aversa, Davide, author. Unity artificial intelligence programming : add powerful, believable, and fun AI entities in your game with the power of Unity 2018! / Dr. Davide Aversa, Aung Sithu Kyaw, Clifford Peters. Fourth edition. Birmingham, UK : Packt Publishing, 2018. 1 online resource (1 volume) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Online resource; title from title page (Safari, viewed February 1, 2019). Includes bibliographical references. To get the most out of this book -- Get in touch -- Introduction to AI -- Artificial Intelligence (AI) -- AI in games -- AI techniques -- Summary -- Finite State Machines -- The player's tank -- Initialization -- Shooting bullet -- Controlling the tank -- The Bullet class -- Setting up waypoints -- The abstract FSM class -- The enemy tank AI -- The Patrol state -- The Chase state -- The Attack state -- The Dead state -- Taking damage -- Using an FSM framework -- The AdvanceFSM class -- The FSMState class -- The state classes -- The PatrolState class -- The NPCTankController class -- Summary -- Randomness and Probability -- Randomness in games -- Definitions of probability -- Character personalities -- FSM with probability -- Dynamic AI -- Demo slot machine -- Summary -- Further reading -- Implementing Sensors -- Basic sensory systems -- Scene setup -- The player's tank and the aspect class -- AI characters -- Testing -- Summary -- Flocking -- Basic flocking behavior -- Individual behavior -- Controller -- Alternative implementation -- FlockController -- Summary -- Path-Following and Steering Behaviors -- Following a path -- Path script -- Path-following agents -- Avoiding obstacles -- Adding a custom layer -- Obstacle avoidance -- Summary -- A* Pathfinding -- Revisiting the A* algorithm -- Implementing the A* algorithm -- Node -- PriorityQueue -- The GridManager class -- The AStar class -- The TestCode class -- Setting up the scene -- Testing the pathfinder -- Summary -- Navigation Mesh -- Setting up the map -- Navigation static -- Baking the navigation mesh -- NavMesh agent -- Updating an agents' destinations -- Scene with slope -- Navigation areas -- Off Mesh Links -- Generated Off Mesh Links -- Manual Off Mesh Links -- Summary -- Behavior Trees -- Introduction to Behavior Trees -- A simple example - patrolling robot -- Implementing a BT in Unity with Behavior Bricks -- Set up the scene -- Implement a Day/Night cycle -- Design the Enemy Behavior -- Implement the Nodes -- Building the Tree -- Attach the BT to the Enemy -- Summary -- External Resources -- Machine Learning in Unity -- The Unity Machine Learning Agents Toolkit -- How to install the ML-Agents Toolkit -- Installing Python and TensorFlow on Windows -- Installing Python and TensorFlow on macOS and Unix-like systems -- Using the ML-Agents Toolkit - a basic example -- Creating the scene -- Implementing the code -- Adding the final touches -- Training a Brain object -- Training the agent -- Summary -- Further reading -- Putting It All Together -- Basic game structure -- Adding automated navigation -- Creating the NavMesh -- Setting up the agent -- Fixing the GameManager script -- Creating decision-makingAI with FSM -- Summary. Learn and Implement game AI in Unity 2018 to build smart game environments and enemies with A*, Finite State Machines, Behavior Trees and NavMesh. Key Features Build richer games by learning the essential concepts in AI for games like Behavior Trees and Navigation Meshes Implement character behaviors and simulations using the Unity Machine Learning toolkit Explore the latest Unity 2018 features to make implementation of AI in your game easier Book Description Developing Artificial Intelligence (AI) for game characters in Unity 2018 has never been easier. Unity provides game and app developers with a variety of tools to implement AI, from the basic techniques to cutting-edge machine learning-powered agents. Leveraging these tools via Unity's API or built-in features allows limitless possibilities when it comes to creating your game's worlds and characters. This fourth edition with Unity will help you break down AI into simple concepts to give you a fundamental understanding of the topic to build upon. Using a variety of examples, the book then takes those concepts and walks you through actual implementations designed to highlight key concepts and features related to game AI in Unity. Further on, you'll learn how to distinguish the state machine pattern and implement one of your own. This is followed by learning how to implement a basic sensory system for your AI agent and coupling it with a Finite State Machine (FSM). Next, you'll learn how to use Unity's built-in NavMesh feature and implement your own A* pathfinding system. You'll then learn how to implement simple ?ocks and crowd dynamics, which are key AI concepts in Unity. Moving on, you'll learn how to implement a behavior tree through a game-focused example. Lastly, you'll apply all the concepts in the book to build a popular game. What you will learn Create smarter game worlds and characters with C# programming Apply automated character movement using pathfinding and steering behaviors Implement non-player character decision-making algorithms using Behavior Trees and FSMs Build believable and highly efficient artificial flocks and crowds Create sensory systems for your AI with the most commonly used techniques Construct decision-making systems to make agents take different actions Explore the application of machine learning in Unity Who this book is for This book is intended for Unity developers with a basic understanding of C# and the Unity editor. Whether you're looking to build your f... Unity (Electronic resource) http://id.loc.gov/authorities/names/n2011038776 Unity (Electronic resource) fast Video games Programming. http://id.loc.gov/authorities/subjects/sh95003476 Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Three-dimensional display systems. http://id.loc.gov/authorities/subjects/sh85135021 Artificial Intelligence https://id.nlm.nih.gov/mesh/D001185 Jeux vidéo Programmation. Intelligence artificielle. Affichage tridimensionnel. artificial intelligence. aat three-dimensional. aat Artificial intelligence fast Video games Programming fast Three-dimensional display systems fast Kyaw, Aung Sithu, author. Peters, Clifford, author. FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1950562 Volltext |
| spellingShingle | Aversa, Davide Kyaw, Aung Sithu Peters, Clifford Unity artificial intelligence programming : add powerful, believable, and fun AI entities in your game with the power of Unity 2018! / To get the most out of this book -- Get in touch -- Introduction to AI -- Artificial Intelligence (AI) -- AI in games -- AI techniques -- Summary -- Finite State Machines -- The player's tank -- Initialization -- Shooting bullet -- Controlling the tank -- The Bullet class -- Setting up waypoints -- The abstract FSM class -- The enemy tank AI -- The Patrol state -- The Chase state -- The Attack state -- The Dead state -- Taking damage -- Using an FSM framework -- The AdvanceFSM class -- The FSMState class -- The state classes -- The PatrolState class -- The NPCTankController class -- Summary -- Randomness and Probability -- Randomness in games -- Definitions of probability -- Character personalities -- FSM with probability -- Dynamic AI -- Demo slot machine -- Summary -- Further reading -- Implementing Sensors -- Basic sensory systems -- Scene setup -- The player's tank and the aspect class -- AI characters -- Testing -- Summary -- Flocking -- Basic flocking behavior -- Individual behavior -- Controller -- Alternative implementation -- FlockController -- Summary -- Path-Following and Steering Behaviors -- Following a path -- Path script -- Path-following agents -- Avoiding obstacles -- Adding a custom layer -- Obstacle avoidance -- Summary -- A* Pathfinding -- Revisiting the A* algorithm -- Implementing the A* algorithm -- Node -- PriorityQueue -- The GridManager class -- The AStar class -- The TestCode class -- Setting up the scene -- Testing the pathfinder -- Summary -- Navigation Mesh -- Setting up the map -- Navigation static -- Baking the navigation mesh -- NavMesh agent -- Updating an agents' destinations -- Scene with slope -- Navigation areas -- Off Mesh Links -- Generated Off Mesh Links -- Manual Off Mesh Links -- Summary -- Behavior Trees -- Introduction to Behavior Trees -- A simple example - patrolling robot -- Implementing a BT in Unity with Behavior Bricks -- Set up the scene -- Implement a Day/Night cycle -- Design the Enemy Behavior -- Implement the Nodes -- Building the Tree -- Attach the BT to the Enemy -- Summary -- External Resources -- Machine Learning in Unity -- The Unity Machine Learning Agents Toolkit -- How to install the ML-Agents Toolkit -- Installing Python and TensorFlow on Windows -- Installing Python and TensorFlow on macOS and Unix-like systems -- Using the ML-Agents Toolkit - a basic example -- Creating the scene -- Implementing the code -- Adding the final touches -- Training a Brain object -- Training the agent -- Summary -- Further reading -- Putting It All Together -- Basic game structure -- Adding automated navigation -- Creating the NavMesh -- Setting up the agent -- Fixing the GameManager script -- Creating decision-makingAI with FSM -- Summary. Unity (Electronic resource) http://id.loc.gov/authorities/names/n2011038776 Unity (Electronic resource) fast Video games Programming. http://id.loc.gov/authorities/subjects/sh95003476 Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Three-dimensional display systems. http://id.loc.gov/authorities/subjects/sh85135021 Artificial Intelligence https://id.nlm.nih.gov/mesh/D001185 Jeux vidéo Programmation. Intelligence artificielle. Affichage tridimensionnel. artificial intelligence. aat three-dimensional. aat Artificial intelligence fast Video games Programming fast Three-dimensional display systems fast |
| subject_GND | http://id.loc.gov/authorities/names/n2011038776 http://id.loc.gov/authorities/subjects/sh95003476 http://id.loc.gov/authorities/subjects/sh85008180 http://id.loc.gov/authorities/subjects/sh85135021 https://id.nlm.nih.gov/mesh/D001185 |
| title | Unity artificial intelligence programming : add powerful, believable, and fun AI entities in your game with the power of Unity 2018! / |
| title_auth | Unity artificial intelligence programming : add powerful, believable, and fun AI entities in your game with the power of Unity 2018! / |
| title_exact_search | Unity artificial intelligence programming : add powerful, believable, and fun AI entities in your game with the power of Unity 2018! / |
| title_full | Unity artificial intelligence programming : add powerful, believable, and fun AI entities in your game with the power of Unity 2018! / Dr. Davide Aversa, Aung Sithu Kyaw, Clifford Peters. |
| title_fullStr | Unity artificial intelligence programming : add powerful, believable, and fun AI entities in your game with the power of Unity 2018! / Dr. Davide Aversa, Aung Sithu Kyaw, Clifford Peters. |
| title_full_unstemmed | Unity artificial intelligence programming : add powerful, believable, and fun AI entities in your game with the power of Unity 2018! / Dr. Davide Aversa, Aung Sithu Kyaw, Clifford Peters. |
| title_short | Unity artificial intelligence programming : |
| title_sort | unity artificial intelligence programming add powerful believable and fun ai entities in your game with the power of unity 2018 |
| title_sub | add powerful, believable, and fun AI entities in your game with the power of Unity 2018! / |
| topic | Unity (Electronic resource) http://id.loc.gov/authorities/names/n2011038776 Unity (Electronic resource) fast Video games Programming. http://id.loc.gov/authorities/subjects/sh95003476 Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Three-dimensional display systems. http://id.loc.gov/authorities/subjects/sh85135021 Artificial Intelligence https://id.nlm.nih.gov/mesh/D001185 Jeux vidéo Programmation. Intelligence artificielle. Affichage tridimensionnel. artificial intelligence. aat three-dimensional. aat Artificial intelligence fast Video games Programming fast Three-dimensional display systems fast |
| topic_facet | Unity (Electronic resource) Video games Programming. Artificial intelligence. Three-dimensional display systems. Artificial Intelligence Jeux vidéo Programmation. Intelligence artificielle. Affichage tridimensionnel. artificial intelligence. three-dimensional. Artificial intelligence Video games Programming Three-dimensional display systems |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1950562 |
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