Practical game AI programming

Written in a conversational tone, this classroom-tested text introduces the fundamentals of linear programming and game theory, showing readers how to apply serious mathematics to practical real-life questions by modelling linear optimization problems and strategic games. The treatment of linear programming includes two distinct graphical methods. The game theory chapters include a novel proof of the minimax theorem for 2x2 zero-sum games. In addition to zero-sum games, the text presents variable-sum games, ordinal games, and n-player games as the natural result of relaxing or modifying the assumptions of zero-sum games. All concepts and techniques are derived from motivating examples, building in complexity, which encourages students to think creatively and leads them to understand how the mathematics is applied. With no prerequisite besides high school algebra, the text will be useful to motivated high school students and undergraduates studying business, economics, mathematics, and

A major revision of the international bestseller on game programming!Graphics hardware has evolved enormously in the last decade. Hardware can now be directly controlled through techniques such as sha

A comprehensive survey of artificial intelligence algorithms and programming organization for robot systems, combining theoretical rigor and practical applications.This textbook offers a comprehensive

"This in-depth, practical guide describes high-performance computing on general purpose graphics processing units (GPGPUs) using DirectX 11. Suitable for game developers and computing professionals, t

Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the design of knowledge-intensive software systems capable of performing intelligent tasks. Using logical and probabilistic formalisms based on answer set programming (ASP) and action languages, this book shows how knowledge-intensive systems can be given knowledge about the world and how it can be used to solve non-trivial computational problems. The authors maintain a balance between mathematical analysis and practical design of intelligent agents. All the concepts, such as answering queries, planning, diagnostics, and probabilistic reasoning, are illustrated by programs of ASP. The text can be used for AI-related undergraduate and graduate classes and by researchers who would like to learn more about ASP and knowledge representation.

The focus of this book is on mathematical programming which combines elements of hierarchical optimization and game theory. The basic model addresses the problem where two decision makers, each with

Based around a theme of the construction of a game engine, this textbook is for final year undergraduate and graduate students, emphasising formal methods in writing robust code quickly. This book takes an unusual, engineering-inspired approach to illuminate the creation and verification of large software systems. Where other textbooks discuss business practices through generic project management techniques or detailed rigid logic systems, this book examines the interaction between code in a physical machine and the logic applied in creating the software. These elements create an informal and rigorous study of logic, algebra, and geometry through software. Assuming prior experience with C, C++, or Java programming languages, chapters introduce UML, OCL, and Z from scratch. Extensive worked examples motivate readers to learn the languages through the technical side of software science.

1.Covers not only AI theory, but modern applications e.g., game programming, machine learning, swarming, artificial immune systems, genetic algorithms, pattern recognition, numerical optimization, dat