I think your current design will end up rewarding the 100⁄0 case more than warranted when there happens to be an assisination at 8 PM, and punishing it less than warranted when the 99% chance doesn’t happen. If the actual odds are 99%, 99.9% and 90% should have the same score.
Or were you intending to deny the closure of rewarding someone for correctly predicting a 5% chance that the sniper will hit when the sniper rolls a natural 20?
The mechanics definitely need to be such that the dominant strategy is to give accurate predictions. I am reminded of Yvain’s post on Nash Equilibria and Schelling Points, in which the optimal strategy is to attack/defend each of the cities in proportion to the values of the cities in question. One of the keys is that it is a repeated trial, which the idea of assassination at 8 does not have.
Although, it does sound as if the computer will be tracking the likelihoods by itself, and you only have to decide what to do with the information produced by the fully updated Bayes net. So maybe one of the key skills will be assessing Value of Information.
Is the objective to teach thin-slicing (getting a feel for the magnitude of the answer without doing the math)? Part of my assumption was that the player would not be given the odds that A is lying about what B said, but might be prompted to think about that possibility.
I think your current design will end up rewarding the 100⁄0 case more than warranted when there happens to be an assisination at 8 PM, and punishing it less than warranted when the 99% chance doesn’t happen. If the actual odds are 99%, 99.9% and 90% should have the same score.
Or were you intending to deny the closure of rewarding someone for correctly predicting a 5% chance that the sniper will hit when the sniper rolls a natural 20?
The mechanics definitely need to be such that the dominant strategy is to give accurate predictions. I am reminded of Yvain’s post on Nash Equilibria and Schelling Points, in which the optimal strategy is to attack/defend each of the cities in proportion to the values of the cities in question. One of the keys is that it is a repeated trial, which the idea of assassination at 8 does not have.
Although, it does sound as if the computer will be tracking the likelihoods by itself, and you only have to decide what to do with the information produced by the fully updated Bayes net. So maybe one of the key skills will be assessing Value of Information.
Is the objective to teach thin-slicing (getting a feel for the magnitude of the answer without doing the math)? Part of my assumption was that the player would not be given the odds that A is lying about what B said, but might be prompted to think about that possibility.