Unity 2018 Artificial Intelligence Cookbook, 2nd Edition

Unity 2018 Artificial Intelligence Cookbook, 2nd Edition
Unity 2018 Artificial Intelligence Cookbook, 2nd Edition by Jorge Palacios
English | 2018 | ISBN: 1788626170 | 334 Pages | EPUB | 10 MB

Unity 2018 Artificial Intelligence Cookbook: Over 90 recipes to build and customize AI entities for your games with Unity, 2nd Edition
Explore various recipes to build games using popular artificial intelligence techniques and algorithms such as Navmesh navigation A*, DFS, and UCB1
Interactive and engaging games come with intelligent enemies, and this intellectual behavior is combined with a variety of techniques collectively referred to as Artificial Intelligence. Exploring Unity’s API, or its built-in features, allows limitless possibilities when it comes to creating your game’s worlds and characters. This cookbook covers both essential and niche techniques to help you take your AI programming to the next level.
To start with, you’ll quickly run through the essential building blocks of working with an agent, programming movement, and navigation in a game environment, followed by improving your agent’s decision-making and coordination mechanisms – all through hands-on examples using easily customizable techniques. You’ll then discover how to emulate the vision and hearing capabilities of your agent for natural and humanlike AI behavior, and later improve the agents with the help of graphs. This book also covers the new navigational mesh with improved AI and pathfinding tools introduced in the Unity 2018 update. You’ll empower your AI with decision-making functions by programming simple board games, such as tic-tac-toe and checkers, and orchestrate agent coordination to get your AIs working together as one.
By the end of this book, you’ll have gained expertise in AI programming and developed creative and interactive games.
What you will learn

  • Create intelligent pathfinding agents with popular AI techniques such as A* and A*mbush
  • Implement different algorithms for adding coordination between agents and tactical algorithms for different purposes
  • Simulate senses so agents can make better decisions, taking account of the environment
  • Explore different algorithms for creating decision-making agents that go beyond simple behaviors and movement
  • Create coordination between agents and orchestrate tactics when dealing with a graph or terrain
  • Implement waypoints by making a manual selector