Is there a simple “continuous” description of the class of objects that LI belongs to, which shows the point of departure from Bayes without relying on all details of LI? (For example, “it’s like a prior but the result also depends on ordering of input facts”.)
You can generalize LI to arbitrary collections of hypotheses, and interpret it as being about bit sequences rather logic, but not much more than that.
The reason the LI paper talks about the LI criterion rather than a specific algorithm is to push in that direction, but it is not as clean as your example.
I’m not sure I understand the question correctly, but what “LI” actually depends on is, more or less, a collection of traders plus a “prior” over them (although you can’t interpret it as an actual prior since more than one trader can be important in understanding a given environment). Plus there is some ambiguity in the process of choosing fixed points (because there might be multiple fixed points).
Is there a simple “continuous” description of the class of objects that LI belongs to, which shows the point of departure from Bayes without relying on all details of LI? (For example, “it’s like a prior but the result also depends on ordering of input facts”.)
Not really.
You can generalize LI to arbitrary collections of hypotheses, and interpret it as being about bit sequences rather logic, but not much more than that.
The reason the LI paper talks about the LI criterion rather than a specific algorithm is to push in that direction, but it is not as clean as your example.
I’m not sure I understand the question correctly, but what “LI” actually depends on is, more or less, a collection of traders plus a “prior” over them (although you can’t interpret it as an actual prior since more than one trader can be important in understanding a given environment). Plus there is some ambiguity in the process of choosing fixed points (because there might be multiple fixed points).