I agree that choosing an action randomly (with higher probability for good actions) is a good way to create a fuzzy satisficer. Do you have any insights into how to:
create queries for planning that don’t suffer from “wishful thinking”, with or without nested queries. Basically the problem is that if I want an action conditioned on receiving a high utility (e.g. we have a factor on the expected utility node U equal to e^(alpha * U) ), then we are likely to choose high-variance actions while inferring that the rest of the model works out such that these actions return high utilities
extend this to sequential planning without nested nested nested nested nested nested queries
I agree that choosing an action randomly (with higher probability for good actions) is a good way to create a fuzzy satisficer. Do you have any insights into how to:
create queries for planning that don’t suffer from “wishful thinking”, with or without nested queries. Basically the problem is that if I want an action conditioned on receiving a high utility (e.g. we have a factor on the expected utility node U equal to e^(alpha * U) ), then we are likely to choose high-variance actions while inferring that the rest of the model works out such that these actions return high utilities
extend this to sequential planning without nested nested nested nested nested nested queries