Unity Artificial Intelligence Programming

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Beginning Game AI with Unity

Game developers will use this book to gain a basic knowledge of programming artificial intelligence using Unity and C#. You will not be bored learning the theory underpinning AI. Instead, you will learn by experience and practice, and complete an engaging project in each chapter. AI is the one of the most popular subjects in gaming today, ranging from controlling the behavior of non-player characters to procedural generated levels. This book starts with an introduction to AI and its use in games. Basic moving behaviors and pathfinding are covered, and then you move through more complex concepts of pathfinding and decision making. What You Will Learn Understand the fundamentals of AI Create gameplay-based AI to address navigation and decision-making problems Put into practice graph theory and behavior models Address pathfinding problems Use the A* algorithm, the deus ex machina of pathfinding algorithms Create a mini stealth game Who This Book Is For Developers and programming enthusiasts with a basic knowledge of Unity and C# who want to understand and master the foundations of artificial intelligence in games
Learn Unity ML-Agents – Fundamentals of Unity Machine Learning

Author: Micheal Lanham
language: en
Publisher: Packt Publishing Ltd
Release Date: 2018-06-30
Transform games into environments using machine learning and Deep learning with Tensorflow, Keras, and Unity Key Features Learn how to apply core machine learning concepts to your games with Unity Learn the Fundamentals of Reinforcement Learning and Q-Learning and apply them to your games Learn How to build multiple asynchronous agents and run them in a training scenario Book Description Unity Machine Learning agents allow researchers and developers to create games and simulations using the Unity Editor, which serves as an environment where intelligent agents can be trained with machine learning methods through a simple-to-use Python API. This book takes you from the basics of Reinforcement and Q Learning to building Deep Recurrent Q-Network agents that cooperate or compete in a multi-agent ecosystem. You will start with the basics of Reinforcement Learning and how to apply it to problems. Then you will learn how to build self-learning advanced neural networks with Python and Keras/TensorFlow. From there you move o n to more advanced training scenarios where you will learn further innovative ways to train your network with A3C, imitation, and curriculum learning models. By the end of the book, you will have learned how to build more complex environments by building a cooperative and competitive multi-agent ecosystem. What you will learn Develop Reinforcement and Deep Reinforcement Learning for games. Understand complex and advanced concepts of reinforcement learning and neural networks Explore various training strategies for cooperative and competitive agent development Adapt the basic script components of Academy, Agent, and Brain to be used with Q Learning. Enhance the Q Learning model with improved training strategies such as Greedy-Epsilon exploration Implement a simple NN with Keras and use it as an external brain in Unity Understand how to add LTSM blocks to an existing DQN Build multiple asynchronous agents and run them in a training scenario Who this book is for This book is intended for developers with an interest in using Machine learning algorithms to develop better games and simulations with Unity. The reader will be required to have a working knowledge of C# and a basic understanding of Python.
Unity Artificial Intelligence Programming

Author: Dr. Davide Aversa
language: en
Publisher: Packt Publishing Ltd
Release Date: 2022-03-28
Learn and implement game AI in Unity to build smart environments and enemies with A* pathfinding, finite state machines, behavior trees, and the NavMesh Key Features Explore the latest Unity features to make AI implementation in your game easier Build richer and more dynamic games using AI concepts such as behavior trees and navigation meshes Implement character behaviors and simulations using the Unity Machine Learning toolkit Book DescriptionDeveloping artificial intelligence (AI) for game characters in Unity has never been easier. Unity provides game and app developers with a variety of tools to implement AI, from basic techniques to cutting-edge machine learning-powered agents. Leveraging these tools via Unity's API or built-in features allows limitless possibilities when it comes to creating game worlds and characters. The updated fifth edition of Unity Artificial Intelligence Programming starts by breaking down AI into simple concepts. Using a variety of examples, the book then takes those concepts and walks you through actual implementations designed to highlight key concepts and features related to game AI in Unity. As you progress, you’ll learn how to implement a finite state machine (FSM) to determine how your AI behaves, apply probability and randomness to make games less predictable, and implement a basic sensory system. Later, you’ll understand how to set up a game map with a navigation mesh, incorporate movement through techniques such as A* pathfinding, and provide characters with decision-making abilities using behavior trees. By the end of this Unity book, you’ll have the skills you need to bring together all the concepts and practical lessons you’ve learned to build an impressive vehicle battle game.What you will learn Understand the basics of AI in game design Create smarter game worlds and characters with C# programming Apply automated character movement using pathfinding algorithm behaviors Implement character decision-making algorithms using behavior trees Build believable and highly efficient artificial flocks and crowds Create sensory systems for your AI world Become well-versed with the basics of procedural content generation Explore the application of machine learning in Unity Who this book is for This Unity artificial intelligence book is for Unity developers with a basic understanding of C# and the Unity Editor who want to expand their knowledge of AI Unity game development.