It’s a little hard to tell from the lack of docs, but you’re modelling dilemmas with Bayesian networks? I considered that, but wasn’t sure how to express Sleeping Beauty nicely, whereas it’s easy to express (and gives the right answers) in my tree-shaped dilemmas. Have you tried to express Sleeping Beauty?
And have you tried to express a dilemma like smoking lesion where the action that an agent takes is not the action their decision theory tells them to take? My guess is that this would be as easy as having a chain of two probabilistic events, where the first one is what the decision theory says to do and the second one is what the agent actually does, but I don’t see any of this kind of dilemma in your test cases.
FWIW we implemented the FDT, CDT, and EDT in Haskell a while ago.
https://github.com/DecisionTheory/DecisionTheory
Oh, excellent!
It’s a little hard to tell from the lack of docs, but you’re modelling dilemmas with Bayesian networks? I considered that, but wasn’t sure how to express Sleeping Beauty nicely, whereas it’s easy to express (and gives the right answers) in my tree-shaped dilemmas. Have you tried to express Sleeping Beauty?
And have you tried to express a dilemma like smoking lesion where the action that an agent takes is not the action their decision theory tells them to take? My guess is that this would be as easy as having a chain of two probabilistic events, where the first one is what the decision theory says to do and the second one is what the agent actually does, but I don’t see any of this kind of dilemma in your test cases.