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Artificial Intelligence for Computer Games (Paperback, 2011 ed.) Loot Price: R4,441
Discovery Miles 44 410
Artificial Intelligence for Computer Games (Paperback, 2011 ed.): Pedro Antonio Gonzalez Calero, Marco Antonio Gomez-Martin

Artificial Intelligence for Computer Games (Paperback, 2011 ed.)

Pedro Antonio Gonzalez Calero, Marco Antonio Gomez-Martin

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Loot Price R4,441 Discovery Miles 44 410 | Repayment Terms: R416 pm x 12*

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The book presents some of the most relevant results from academia in the area of Artificial Intelligence for games. It emphasizes well theoretically supported work supported by developed prototypes, which should lead into integration of academic AI techniques into current electronic entertainment games. The book elaborates on the main results produced in Academia within the last 10 years regarding all aspects of Artificial Intelligence for games, including pathfinding, decision making, and learning. A general theme of the book is the coverage of techniques for facilitating the construction of flexible not prescripted AI for agents in games. Regarding pathfinding, the book includes new techniques for implementing real-time search methods that improve the results obtained through AI, as well as techniques for learning pathfinding behavior by observing actual players. Regarding decision making, the book describes new techniques for authoring tools that facilitate the construction by game designers (typically nonprogrammers) of behavior controlling software, by reusing patterns or actual cases of past behavior. Additionally, the book will cover a number of approaches proposed for extending the essentially pre-scripted nature of current commercial videogames AI into a more interactive form of narrative, where the story emerges from the interaction with the player. Some of those approaches rely on a layered architecture for the character AI, including beliefs, intentions and emotions, taking ideas from research on agent systems. The book also includes chapters on techniques for automatically or semiautomatically learning complex behavior from recorded traces of human or automatic players using different combinations of reinforcement learning, case-based reasoning, neural networks and genetic algorithms.

General

Imprint: Springer-Verlag New York
Country of origin: United States
Release date: October 2014
First published: 2011
Editors: Pedro Antonio Gonzalez Calero • Marco Antonio Gomez-Martin
Dimensions: 235 x 155 x 11mm (L x W x T)
Format: Paperback
Pages: 200
Edition: 2011 ed.
ISBN-13: 978-1-4939-0053-4
Categories: Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers
Books > Computing & IT > Applications of computing > Artificial intelligence > General
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LSN: 1-4939-0053-6
Barcode: 9781493900534

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