Our set of possible worlds comes from somewhere, some sort of criteria. Whatever generates that list passes it to our choice algorithm, which begins branching. Lets say we receive an observation that contains both Logical and Indexical updates- could we not just take our current set of possible worlds, with our current set of data on them, update the list against our logical update, and pass that list on to a new copy of the function? The collection remains fixed as far as each copy of the function is concerned, but retains the ability to update on new information. When finished, the path returned will be the most likely given all new observations.
Our set of possible worlds comes from somewhere, some sort of criteria. Whatever generates that list passes it to our choice algorithm, which begins branching. Lets say we receive an observation that contains both Logical and Indexical updates- could we not just take our current set of possible worlds, with our current set of data on them, update the list against our logical update, and pass that list on to a new copy of the function? The collection remains fixed as far as each copy of the function is concerned, but retains the ability to update on new information. When finished, the path returned will be the most likely given all new observations.