If a simulation of poker looses money in a way that is similar to a game of poker, it is a good simulation because it will allow for more accurate worst-case budgeting.
You mean, if an agent loses money. And that’s the point; if the only thing you know is that an agent loses money in a simulation of poker, how can you prove the same is true for real poker?
I think Karl Popper made the the best case that there are no final proofs, only provisional, and that the way to find the more useful provisional proofs is to note how they fail and not how they succeed. A poker simulator that can tell me accurately how much I might loose is more helpful than one that tells me how much I might win. I can budget based on the former and not the later.
If you want final proofs (models, theories, simulations) the answer is there are no scientific final proofs.
I could be wrong, or perhaps i have answered a question not asked.
It is more likely a simulation simulates X if it fails like X fails than if it fails in a different way.
i’m not sure I understand what you mean by ‘failing’ in regards to simulations. Could you elaborate?
If a simulation of poker looses money in a way that is similar to a game of poker, it is a good simulation because it will allow for more accurate worst-case budgeting.
You mean, if an agent loses money. And that’s the point; if the only thing you know is that an agent loses money in a simulation of poker, how can you prove the same is true for real poker?
I think Karl Popper made the the best case that there are no final proofs, only provisional, and that the way to find the more useful provisional proofs is to note how they fail and not how they succeed. A poker simulator that can tell me accurately how much I might loose is more helpful than one that tells me how much I might win. I can budget based on the former and not the later.
If you want final proofs (models, theories, simulations) the answer is there are no scientific final proofs.
I could be wrong, or perhaps i have answered a question not asked.