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Explanation About FuSM in Brain's Schwab Book

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Hi all, while I'm reading "AI Game Engine Programming" for Brain Schwab, in the FuSM Chapter he said the following (page 281): "It should be noted that FuSMs build on the notion of fuzzy logic but don't represent actual fuzzy logic system" Can anyone explain what this means? Thanks in advance :)

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In traditional logic, there are only two possible end values: TRUE and FALSE. An extension on this is called "multi-valued logic" where the possible values can be whatever is defined within the given system. In mathematics, "fuzzy logic" is a multi-valued logic designed to deal with reasoning problems that include information of an approximate nature. In essence, it is a branch of set theory wherein the membership of any given set is stated as a number of functions, instead of the more "crisp" membership of traditional logic (meaning, you're in the set or not).

The metaphor, then, for game AI state machines to call themselves fuzzy is that an AI agent can engage a particular behavior in a fuzzy manner; the behavior is not just ON or OFF. It is instead activated to some amount as necessary.

That make more sense?

Feel free to ask any questions you want about "AI Game Engine Programming," I'm the author and I'll try to answer if I see the question pop up.

Thanks for buying the book, and being interested in game AI.

Brian

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I have "AI Game Engine Programming" too, helped me alot,
thanx Brian.

Now maybe I will try "Behavioral Mathematics for Game AI"
too. Can never resist things listed in the signature...

P.S. is there a way to hide signatures in the post?

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