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Behavioral Mathematics for Game AI by Dave Mark

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16. Variation in Choice

In the past few chapters, all of our examples have been solved by finding “the best” answer to the problem. We built all of our utility functions to rate and score the aspects of the decision, sorted the options by the score, and selected the one with “the best” score (be that highest or lowest). Naturally, this sounds strikingly like normative (or prescriptive) decision theory. In fact, if we recast it in the vernacular we used in Chapter 4, we were determining what we should do. Remember that normative decision theory assumes that our agent:

  • Has all of the relevant information available

  • Is able to perceive the information with the accuracy needed

  • Is able to perfectly perform all the calculations necessary to apply those ...

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