Binary Trees MINI MAXING, probability trees

This is a discussion on Binary Trees MINI MAXING, probability trees within the General AI Programming forums, part of the Cprogramming.com and AIHorizon.com's Artificial Intelligence Boards category; Could anyone explain in english the basic idea behind these topics. The purpose of this thread is to get local ...

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    Binary Trees MINI MAXING, probability trees

    Could anyone explain in english the basic idea behind these topics.
    The purpose of this thread is to get local Cprogrammers input and to increase interest in this topic.

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    /Bump the bum.

    My take, many years ago I read a book on artificial intelligence and my memory is poor but here goes.

    Binary trees are often used because you may quickly search for any given data.
    The idea behind probability trees is to find the highest or lowest probability quickly. MINI MAXING means the data on the branches of the tree are weighted based on there distance from the root, and staticaly by the probability based on its distance (and often position depending on your traversal method) from the root. The weighted numbers are essentialy odds, while the position is a guess based on the odds.

    I invite any comments because it has been so long that I feel very shaky even replying under my own post.

    It is evident that these terms may be looked up via a search engine.

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    Binary trees are often used because you may quickly search for any given data.
    They are, however, memory inefficient.
    dwk

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    I had to do a project using the minimax algo for an AI class, I initially designed it using trees but it was ungodly slow, then I just did it as a couple of functions in C, which was a lot faster yet harder to read.

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