Download e-book for kindle: Artificial Intelligence for Games, Second Edition by Ian Millington, John Funge

By Ian Millington, John Funge

ISBN-10: 0123747317

ISBN-13: 9780123747310

Nearly all of software program improvement books, even if it's for line-of-business app dev or online game improvement, appear to have little to no details that may be discovered through an off-the-cuff web search.

This booklet is among the few exceptions. there's a fresh breadth and intensity of video game AI wisdom during this booklet that has been of super support. not like the typical "Gems" sequence of books, this booklet comprises adequate info on approximately each subject for the reader to construct a 'ground up' implementation in their own.

My basically proceedings are that the pseudocode appears overly simplified and never as simply switched over to a concrete implementation as i might like, and that even for a booklet on game-specific AI implementations, the authors appear to get pleasure from a section extra of an academic/idealized method of the layout. that would be much less bothersome to a pro online game developer, yet i am on the hobbyist/indie point, and infrequently desire a quick-and-dirty implementation ahead of I start to rather comprehend what is going on.

Having acknowledged that, i used to be capable of use the e-book to benefit approximately and enforce goal-oriented motion making plans, quickly and versatile A* direction discovering (with more information on transformed funnel set of rules online), and a number of other serious elements.

I may totally suggest this ebook.

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Extra info for Artificial Intelligence for Games, Second Edition

Example text

We’ll rely instead on a general indication. Where a complete indication of the complexity is too involved, we’ll indicate the approximate running time or memory in the text, rather than attempt to derive an accurate O() value. Some algorithms have confusing performance characteristics. It is possible to set up highly improbable situations to deliberately make them perform poorly. In regular use (and certainly in any use you’re likely to have in a game), they will have much better performance. When this is the case, we’ve tried to indicate both the expected and the worst case results.

In our experience, full source code listings in the text of a book are rarely useful and often bloat the size of the book dramatically. Most developers use C++ (although a significant but rapidly falling number use C) for their core AI code. In places some of the discussion of data structures and optimizations will assume that you are using C++, because the optimizations are C++ specific. Despite this, there are significant numbers using other languages such as Java, Lisp, Lua, Lingo, ActionScript, or Python, particularly as scripting languages.

Several computing pioneers (such as Turing, von Neumann, and Shannon) were also pioneers in early AI. Turing, in particular, has become an adopted father to the field, as a result of a philosophical paper he published in 1950 [Turing, 1950]. The Symbolic Era From the late 1950s through to the early 1980s the main thrust of AI research was “symbolic” systems. A symbolic system is one in which the algorithm is divided into two components: a set of knowledge (represented as symbols such as words, numbers, sentences, or pictures) and a reasoning algorithm that manipulates those symbols to create new combinations of symbols that hopefully represent problem solutions or new knowledge.

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Artificial Intelligence for Games, Second Edition by Ian Millington, John Funge


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