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AI Game Development: A Practical Guide to Building Modern Games with Artificial Intelligence, Procedural Systems, Intelligent Gameplay, and AI-Powered
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Publisher: Independently Published
Pages: 238
Weight: 0.92
Height: 0.50 Width: 7.50 Depth: 9.25
Language: English
What if you could build game worlds that generate themselves, NPCs that behave intelligently, and development workflows that use AI to do more of the heavy lifting?
Game AI is no longer limited to simple enemies following scripted paths. Modern developers can combine artificial intelligence, procedural systems, machine learning, and generative tools to create games that feel more dynamic, responsive, and alive.
AI Game Development is a practical guide for developers who want to understand how these systems actually work-and how to build them.
Inside, you'll explore the foundations of game AI programming, from deterministic behavior and finite state machines to behavior trees, sensory systems, decision-making, and game AI pathfinding. You'll learn how traditional techniques such as A* and Dijkstra can help game agents navigate complex environments and make intelligent decisions.
But intelligent gameplay is only part of the picture.
You'll also discover how procedural game generation can be used to create terrain, caves, dungeons, ecosystems, loot layouts, and expansive worlds. Learn how seeded randomness, noise functions, cellular automata, L-systems, Binary Space Partitioning, Wave Function Collapse, chunking, caching, and world streaming can work together to create repeatable yet highly varied game environments.
Inside this practical guide, you'll learn how to:
- Build intelligent NPCs and enemy behaviors using traditional game AI techniques
- Implement pathfinding and decision-making systems for dynamic gameplay
- Explore reinforcement learning and machine-learning approaches for game agents
- Create procedural environments, dungeons, ecosystems, and expansive worlds
- Use Python to prototype and simulate AI-driven game systems
- Understand how Unity ML-Agents and learning-based architectures can connect game environments with machine-learning systems
- Explore LLM game development and dynamic dialogue systems for more responsive characters
- Use generative AI throughout the game-development workflow, from asset ideation to prototyping
- Accelerate development with AI-assisted coding, refactoring, and mechanic generation
- Build automated game testing systems that stress-test mechanics and uncover hidden problems
- Analyze playtest telemetry with machine-learning techniques to identify problem areas
- Optimize AI systems through CPU/GPU budgeting, asynchronous processing, multithreading, and data-oriented design
- Understand ECS concepts and how they can support scalable AI-heavy game systems
- Examine copyright, asset provenance, and the practical challenges surrounding AI-generated game content
Whether you're interested in AI-powered game development, procedural systems, intelligent NPCs, machine learning, or modern development automation, this book gives you a structured path through the technologies shaping the next generation of games.
You won't just learn what these technologies are. You'll see how they can be structured, connected, tested, optimized, and applied through practical examples and Python implementations.
Build smarter systems. Generate richer worlds. Prototype faster. Test more intelligently. Push your game development workflow further with AI.
Start exploring AI Game Development today and discover what you can build when intelligent systems become part of your development toolkit.
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