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Practical C++ Game Programming with Data Structures and Algorithms

Practical C++ Game Programming with Data Structures and Algorithms

By : Zhenyu George Li, Charles Shih-I Yeh
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Practical C++ Game Programming with Data Structures and Algorithms

Practical C++ Game Programming with Data Structures and Algorithms

4 (2)
By: Zhenyu George Li, Charles Shih-I Yeh

Overview of this book

Creating responsive, intelligent games takes more than just following engine tutorials. It requires solving real development challenges with practical, efficient code. This book bridges theory and practice with proven algorithms and techniques grounded in real-world production needs, emphasizing clean, portable C++ implementations. Starting with raylib and the custom Knight engine layer, you’ll be introduced to a simple object-oriented scene and game object system. From there, you'll build responsive gameplay systems using essential data structures and algorithms, progressing through 2D rendering, collision detection, effects, and camera control before advancing to 3D graphics environments built using shaders, lighting, quad-tree terrain, and dynamic camera setups. You’ll animate characters using skeletal rigs, interpolation, and inverse kinematics for fluid movement and then develop game AI using FSMs, behavior trees, A* pathfinding, and steering behaviors. The book also covers neural networks, exploring their underlying theories, training processes, and tools. Throughout, the code is written in legacy-compatible C++ to ensure broad support across platforms and compilers. By the end, you’ll have gained the skills to build game systems that not only work but also scale, perform, and adapt like professional-grade code.
Table of Contents (18 chapters)
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Preface
Lock Free Chapter
1
Part I: Data Structure and Algorithm Fundamentals
5
Part II: Graphics Algorithms in Practice
10
Part III: Breathing Life into Your Games
14
Part IV: Reflecting and Moving Forward
16
Other Books You May Enjoy
17
Index

Reviewing the evolution of AI

Artificial intelligence (AI) has evolved from early rule-based systems into powerful technologies that shape today’s world. In the mid-20th century, AI began with symbolic reasoning and expert systems—machines that followed human-defined rules to simulate decision-making in limited contexts.

However, these early systems were constrained by limited computing power and data, making them suitable only for narrow, specialized tasks. A major shift occurred in the 1980s and 1990s, as faster processors, increased storage, and the rise of GPUs enabled AI to handle complex computations and large datasets.

This progress laid the groundwork for the machine learning techniques you’re about to explore in this chapter—systems that learn from data rather than relying solely on pre-programmed rules.

Advancements in computing power and access to data opened the door to a new era of AI: Machine learning (ML). A major breakthrough...

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Practical C++ Game Programming with Data Structures and Algorithms
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