1) The simplest explanation is the most probable, so the distribution of probabilities for hypotheses looks like: 0.75, 0.12, 0.04 …. if hypothesis are ordered from simplest to more complex.
2) The simplest explanation is the just more probable, so the distribution of probabilities for hypotheses looks like: 0.09, 0.07, 0.06, 0.05.
The interesting feature of the second type is that simplest explanation is more likely to be wrong than right (its probability is less than 0.5).
Different types of Occam razor are applicable in different situations. If the simplest hypothesis is significantly simpler than others, it is the first case. If all hypothesis are complex, it is the second. First situation is more applicable some inherently simple models, e.g. laws of physics or games. The second situation is more about complex situation real life.
I’m struggling to think of a situation where on priors (with no other information), I expect the simplest explanation to be more likely than all other situations combined (including the simplest explanation with a tiny nuance).
EY suggested (if I remember correctly) that MWI interpretation of quantum mechanics is true as it is simplest explanation. There are around hundred other more complex interpretations of QM. Thus, in his interpretation, P(MWI) is more than a sum of probabilities of all other interpretations.
What does “all the other explanation s combined” mean as ontology? If they make statements about reality that are mutually incompatible, then they cant all be true.
That doesn’t answer my question as stated … I asked about ontology, you answered about probability.
If a list of theories is exhaustive, which is s big “if”, then one of them is true. And in the continuing absence of a really good explanation of Occams Razor, it doesn’t have to be the simplest.
But that doesn’t address the issue of summing theories, as opposed to summing probabilities.
Ok, tabooing the word ontology here. All that’s needed is an understanding of Bayesianism to answer the question of how you combine the chance of all other explanations.
Two types of Occam’ razor:
1) The simplest explanation is the most probable, so the distribution of probabilities for hypotheses looks like: 0.75, 0.12, 0.04 …. if hypothesis are ordered from simplest to more complex.
2) The simplest explanation is the just more probable, so the distribution of probabilities for hypotheses looks like: 0.09, 0.07, 0.06, 0.05.
The interesting feature of the second type is that simplest explanation is more likely to be wrong than right (its probability is less than 0.5).
Different types of Occam razor are applicable in different situations. If the simplest hypothesis is significantly simpler than others, it is the first case. If all hypothesis are complex, it is the second. First situation is more applicable some inherently simple models, e.g. laws of physics or games. The second situation is more about complex situation real life.
I’m struggling to think of a situation where on priors (with no other information), I expect the simplest explanation to be more likely than all other situations combined (including the simplest explanation with a tiny nuance).
Can you give an example of #1?
EY suggested (if I remember correctly) that MWI interpretation of quantum mechanics is true as it is simplest explanation. There are around hundred other more complex interpretations of QM. Thus, in his interpretation, P(MWI) is more than a sum of probabilities of all other interpretations.
MWI is more than one theory, because everything is more than one thing.
There is an approach based on coherent superpositions, and a version based on decoherence. These are incompatible opposites.
How simple a version of MWI is, depends on how it deals with all the issues, including the basis problem.
What does “all the other explanation s combined” mean as ontology? If they make statements about reality that are mutually incompatible, then they cant all be true.
It means that p(one of them is true) is more than p(simplest explanation is true)
That doesn’t answer my question as stated … I asked about ontology, you answered about probability.
If a list of theories is exhaustive, which is s big “if”, then one of them is true. And in the continuing absence of a really good explanation of Occams Razor, it doesn’t have to be the simplest.
But that doesn’t address the issue of summing theories, as opposed to summing probabilities.
But “all the other explanations combined” was talking about the probabilities. We’re not combining the explanations, that wouldn’t make any sense.
The only ontology that is required is Bayesianism, where explanations can have probabilities of being correct.
Bayesianism isn’t an ontology.
Ok, tabooing the word ontology here. All that’s needed is an understanding of Bayesianism to answer the question of how you combine the chance of all other explanations.