Reproducing Prospect Theory with 'differentiable Decision Theories'

The TLDR of this paper:

You can generalize theories of decision-making into broad functional forms and then apply gradient descent to find the best parameters for that functional form. For example, prospect theory is multiply a utility weighting function U(x) with a probability weighting function p(x). Kahneman and Tversky proposed one specific set of U(x) and p(x), but we can use autodiff to generate all.

We can apply this method to any functional form.

Happy to answer any questions!

And for large sums of money, you don't need prospect theory to explain loss aversion. Plain old marginal utility will do.