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Programming Game AI by Example
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Programming Game AI by Example
Programming Game AI by Example provides a comprehensive and practical introduction to the “bread and butter” AI techniques used by the game development industry.
Programming Game AI by Example
商品＃: 197307345

Programming Game AI by Example

85% of respondents would recommend this to a friend

商品＃: 197307345

TWD 2392

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Programming Game AI by Example provides a comprehensive and practical introduction to the “bread and butter” AI techniques used by the game development industry.
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What Stands Out

Hands-on Approach
Offers practical examples throughout the book that allow readers to implement game AI concepts directly, making complex theories accessible and engaging for beginner to intermediate programmers.
Comprehensive Coverage
Covers a wide range of AI techniques tailored specifically for game development, ensuring readers develop a robust skillset applicable to various genres and platforms.
Expert Insights
Written by industry experts, the book provides valuable insider tips and best practices, enhancing the reader's understanding of real-world applications and improving their game development projects.

產品詳情

Shop Programming Game AI by Example online at a best price in Taiwan. 1556220782
  • Comprehensive and practical introduction to AI techniques used in game development
  • Covers designing, programming, and implementing intelligent agents for action games
  • Focused on using C++ programming language
  • Techniques covered include state- and goal-based behavior, inter-agent communication, steering behaviors, and more
  • Covers topics like graph theory, search, path planning, scripting, perceptual modeling, and fuzzy logic
  • Ideal resource for game developers looking to enhance their AI programming skills
Publisher Jones & Bartlett Learning
Publication date 1 Oct. 2004
Language English
Print length 495 pages
ISBN-10 1556220782
ISBN-13 978-1556220784
Item weight 680 g
Dimensions 16.51 x 2.54 x 22.86 cm
Part of series Wordware Game Developer's Library

Who Should Buy?

Suitable For
  • Aspiring Game Developers

    This book provides practical insights, making it suitable for those wanting to create smarter game characters.

  • Computer Science Students

    Ideal for students learning AI concepts, offering hands-on examples to enhance understanding in a relatable context.

  • Hobbyist Programmers

    Perfect for individuals looking to experiment with AI in games without extensive prior knowledge or experience.

Not Suitable For
  • Advanced AI Researchers

    Not suitable for experts seeking in-depth theoretical analysis or cutting-edge AI methodologies outside game design.

產品描述

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Software Architecture Editorial Review

Programming Game AI By Example is a comprehensive guide published by Jones & Bartlett Learning on October 1, 2004. Spanning 495 pages, it offers insights into AI techniques for game development, particularly beneficial for those looking to implement efficient and intelligent behavior in characters without taxing system resources. Readers have praised its clarity and that it caters well to beginners by not assuming prior knowledge. The practical tutorials focus on key areas like steering behaviors and pathfinding, highlighted as particularly useful chapters. However, some have mentioned the coding examples could be cleaner, noting a preference for pseudo-code to simplify understanding.

Customer Reviews & Ratings

4.6
164 客戶評價
  • 5 星
    71%
  • 4 星
    21%
  • 3 星
    5%
  • 2 星
    1%
  • 1 星
    2%

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優點

  • Clear writing style, easy for beginners to understand.
  • Covers efficient AI techniques without overwhelming resources.
  • Useful chapters on steering behaviors and pathfinding.
  • Practical tutorials with good working examples.
  • Basic maths/physics primer is invaluable for reference.

缺點

  • Coding examples can be messy and challenging to follow.

Product Price History

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TWD 2392

立即訂購並活動它 週二, 十月 13

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特色和優勢

  • Comprehensive and practical introduction to AI techniques for game development
  • Learn designing, programming, and implementing intelligent agents
  • Covers state- and goal-based behavior, inter-agent communication, steering behaviors, and more
  • Includes techniques like graph theory, search, path planning, scripting, and fuzzy logic

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