Unity artificial intelligence programming : add powerful, believable, and fun AI entities in your game with the power of Unity 2018! /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Aversa, Davide (Autor), Kyaw, Aung Sithu (Autor), Peters, Clifford (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing, 2018.
Edición:Fourth edition.
Temas:
Unity (Electronic resource)
Computer games > Programming.
Artificial intelligence.
Three-dimensional display systems.
Artificial Intelligence
Jeux d'ordinateur > Programmation.
Intelligence artificielle.
Affichage tridimensionnel.
artificial intelligence.
three-dimensional.
Video games > Programming.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • 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.

Ejemplares similares