Practical Game AI Programming

Create game AI and implement cutting edge AI algorithms from scratch About This Book * Move beyond using libraries for creating smart game AIs, create your own AI projects from scratch. * Implement latest algorithms for AI development and in-game interaction * Customize your existing game AIs and make them better and efficient and improve your overall game performance. Who This Book Is For The ideal target audience of this book will be game developers with a basic knowledge of game development techniques. They should know some basic programming techniques in wither C# or C++. What you will learn * Explore the vast game genres that exist * Get to know the basics of how to create different AI for different type of games * Discover the probabilities and possibilities of the AI character to determine moves taking in consideration the state of the player * Know what to do when something interferes with the AI choices and how the AI will behave if that happens * Plan the interaction between the AI character and the environment using Smart Zones or Triggering Events * Use animations correctly, blending one animation into another and rather than stopping one animation and starting another * Calculate the best options for the AI to move using Pruning Strategies, Wall Distances, Map Preprocess Implementation, and Forced Neighbours In Detail A smart and diverse game AI is considered to be one of the main pillars of a successful game. This book will help you to get inside game AI programming, implement latest cutting edge algorithms with C#, and finally help you create effective and interesting AI for your game projects. The book starts with the basics examples of AI for different game genres and directly jumps into defining the probabilities and possibilities of the AI character to do determine character movement. Next, you'll learn how AI character should behave within the environment created. Moving on, you'll explore how to work with the animations. You'll also plan and create pruning strategies, and create Theta Algorithms to find short and realistic looking game paths. Next, you'll learn how the AI should behave when having a lot of characters in the same scene. You'll explore what methods and algorithms, such as possibility maps, Forward Chaining Plan, Rete Algorithm, Pruning Strategies, Wall Distances, and Map Preprocess Implementation should be used on different occasions, how to overcome some limitations, and how to deliver a better experience to the player. By the end of the book, you would be able to think differently about AI.