Unity3D游戏AI编程实战指南

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"Unity4.xGameAIProgramming - 通过丰富的示例项目和下一代技术学习并实现Unity3D中的游戏AI编程" 在《Unity4.x Game AI Programming》这本书中,作者Aung Sithu Kyaw、Clifford Peters和Thet Naing Swe深入浅出地介绍了在Unity引擎中实现游戏人工智能的方法和技巧。这本书特别适合对游戏开发感兴趣,特别是想要掌握Unity AI技术的开发者。 Unity是世界上最流行的跨平台游戏开发工具之一,它提供了强大的功能来创建各种类型的游戏,而AI(人工智能)是游戏体验中不可或缺的一部分。本书旨在帮助读者理解和实施Unity3D中的基本和高级AI概念,以提升游戏的交互性和挑战性。 书中内容涵盖了以下关键知识点: 1. **基础AI概念**:介绍游戏AI的基础知识,包括寻路算法(如A*寻路),行为树(Behavior Trees)以及状态机(State Machines),这些都是游戏角色智能行为的基础。 2. **智能体(Agents)**:讲解如何在Unity中创建和配置智能体,包括设置导航网格(Navigation Meshes)以允许AI角色在复杂环境中移动。 3. **决策系统**:探讨如何让AI角色做出合理的决策,包括基于规则的系统(Rule-based Systems)和有限状态机(FSM),以模拟不同情境下的行为。 4. **路径规划与寻路**:详细讲解A*算法和其他寻路技术,以及如何在Unity中实现这些算法以创建动态的环境探索。 5. **群体行为(Swarm Intelligence)**:介绍如何设计群体AI,使得多个AI角色能表现出协调一致的行为,例如模拟鸟群或鱼群的移动。 6. **机器学习应用**:简要讨论如何将机器学习技术如神经网络、遗传算法等应用于游戏AI,为游戏添加更复杂的适应性和学习能力。 7. **战斗与敌方行为**:讲解如何设计敌人AI,包括设定战斗策略、响应玩家行为以及生成动态难度。 8. **示例项目**:书中包含大量示例项目,让读者可以动手实践,通过实际操作理解AI在游戏中的应用。 9. **优化技巧**:提供关于如何优化AI性能的建议,确保游戏在不同设备上的流畅运行。 10. **未来趋势**:探讨游戏AI的最新发展和未来可能的方向,帮助读者保持对行业的了解。 通过这本书,读者不仅可以学习到Unity3D的AI技术,还能了解到游戏AI领域的最新趋势和最佳实践。对于希望提升游戏开发技能,尤其是AI方面的开发者来说,这是一本非常有价值的参考资料。
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Practical Game AI Programming English | 2017 | ISBN-10: 1787122816 | 348 pages | PDF/MOBI/EPUB (conv) | 25 Mb Key Features Move beyond using libraries for creating smart game AIs, create your own AI projects from scratch. Implement latest algorithms for AI development and in-game interaction Customize your existing game AIs and make them better and efficient and improve your overall game performance. Book Description A smart and diverse game AI is considered to be one of the main pillars of a successful game. This book will help you to get inside game AI programming, implement latest cutting edge algorithms with C#, and finally help you create effective and interesting AI for your game projects. 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 do determine character movement. Next, you'll learn how AI character should behave within the environment created. Moving on, you'll explore how to work with the 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 having a lot of characters in the same scene. You'll explore what 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, how to overcome some limitations, and how to deliver a better experience to the player. By the end of the book, you would be able to think differently about AI. What you will learn Explore the vast game genres that exist Get to know the basics of how to create different AI for different type of games Discover the probabilities and possibilities of the AI character to determine moves taking in consideration the state of the player Know what to do when something interferes with the AI choices and how the AI will 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