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I have a set of game characters of a single shape (A) but a different size (small (1) to big (5)) and so the set of characters is (A1A2A3A4A5). They interact with eachother in a game grid in a pair-wise fashion, an interaction during which one will win and one will lose a battle. This goes on for a finite amount of time.

Is there a way I can use Bayesian inference to:

  1. create a ranking of these characters in terms of who has won the most, and
  2. create a variable that represents the gradual acquisition of knowledge about the

difference in size between the characters?

I currently have a list of Beta variables to characterise the rank, and can see how one could possibly use some kind of inference to rank them, but I am unsure as to make the second part work. The size difference needs to be used in some way to inform a variable, but I am unsure beyond that.

So in sum, help greatly appreciated on points 1 and 2.

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Is there any connection between the sizes and the chances of winning or losing a battle? If so, you might want to describe it; if not, how is knowledge about the difference in size acquired? –  joriki Nov 18 '11 at 15:01
Can we assume that if the character size is bigger, there is a higher probability of winning the battle. A size difference is extracted as an output of the battle (call it DH). –  Alan Nov 18 '11 at 15:16

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