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Unity 2018 Artificial Intelligence Cookbook - Second Edition

More Information
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
About

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.

Features
  • Explore different algorithms for creating decision-making agents that go beyond simple behaviors and movement
  • Discover the latest features of the NavMesh API for scripting intelligent behaviour in your game characters
  • Create games that are non-predictable and dynamic and have a high replayability factor
Page Count 334
Course Length 10 hours 1 minutes
ISBN9781788626170
Date Of Publication 27 Aug 2018
Introduction
Predicting actions with an N-Gram predictor
Improving the predictor – Hierarchical N-Gram
Learning to use Naïve Bayes classifier
Implementing reinforcement learning
Implementing artificial neural networks

Authors

Jorge Palacios

Jorge Palacios is a software and game developer with a BS in computer science and eight years of professional experience. He's been developing games for the last five years in different roles, from tool developer to lead programmer. Mainly focused on artificial intelligence and gameplay programming, he is currently working with Unity and HTML5. He's also a game-programming instructor, speaker, and game-jam organizer.