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Год издания: 2017
Автор: DaGraca M.
Издательство: Packt Publishing
Качество: Издательский макет или текст (eBook)
Интерактивное оглавление: Да
Количество страниц: 348
Описание: The book starts with the basics examples of AI for different game genres and directly jumps into defining the probabilities and possibilities of the AI character to determine character movement. Next, you’ll learn how AI characters should behave within the environment created.
Moving on, you’ll explore how to work with animations. You’ll also plan and create pruning strategies, and create Theta algorithms to find short and realistic looking game paths. Next, you’ll learn how the AI should behave when there is a lot of characters in the same scene.
You'll explore which methods and algorithms, such as possibility maps, Forward Chaining Plan, Rete Algorithm, Pruning Strategies, Wall Distances, and Map Preprocess Implementation should be used on different occasions. You’ll discover how to overcome some limitations, and how to deliver a better experience to the player. By the end of the book, you think differently about AI.
What You Will Learn
- Get to know the basics of how to create different AI for different type of games
- Know what to do when something interferes with the AI choices and how the AI should behave if that happens
- Plan the interaction between the AI character and the environment using Smart Zones or Triggering Events
- Use animations correctly, blending one animation into another and rather than stopping one animation and starting another
- Calculate the best options for the AI to move using Pruning Strategies, Wall Distances, Map Preprocess Implementation, and Forced Neighbours
- Create Theta algorithms to the AI to find short and realistic looking paths
- Add many characters into the same scene and make them behave like a realistic crowd
ОглавлениеTable of Contents
1: Different Problems Require Different Solutions
2: Possibility and Probability Maps
3: Production System
4: Environment and AI
5: Animation Behaviors
6: Navigation Behavior and Pathfinding
7: Advanced Pathfinding
8: Crowd Interactions
9: AI Planning and Collision Avoidance
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