|
|
|
|
|
by conistonwater
4126 days ago
|
|
My point is that utility is a rather narrowly-defined concept, so if you find a situation where people don't seem to be maximizing any utility function, one of the possibilities is that the concept of a utility function is too narrowly-defined. Things like anchoring, loss aversion, ambiguity aversion can all be modelled: the only thing you lose is the name "utility function". Maybe the utility function needs to depend on the entire history of states (for loss aversion), or maybe the question being asked is subject to uncertainty, or there is a fundamental amount of model uncertainty. All of those can be modelled in probabilistic terms. So if rational maximization means that people have a utility function that they maximize, then yes, rational maximization is not what people do. But that is partly the fault of how the definition of utility was chosen. |
|
What Kahneman and Tversky observed is that people don't even choose consistently. It depends on how the choices are presented. For instance, whether the subject frames an outcome as a loss or a smaller-than-expected gain. No matter how you define a utility function, it will not always be maximized. So, it's not a question of defining the function less narrowly. You can present two games with mathematically identical sets of outcomes and people consistently rank the outcomes differently.
Anyway, it's a very good and important book, and doesn't have much to do with Bayesian statistics.
[Ninja-edited since HN doesn't let me respond further below...if you can show the outcomes K & T observed are in fact consistent with a more broadly defined utility function, then you too can win a Nobel prize!]