This discussion reminds me of NASA's CLIPS [1], particularly FuzzyCLIPS. I know that is basically a rule engine/expert system basis at its core, but FuzzyCLIPS

This discussion reminds me of NASA's CLIPS [1], particularly FuzzyCLIPS. I know that is basically a rule engine/expert system basis at its core, but FuzzyCLIPS was an interesting variant that try to do inference off of CLIPS rules and facts. I always wondered if rules and facts can be seen as high-order abstractions that represent the low-level data that is encoded into neural nets. Would that mean that a system of symbolic logic, or rules and facts can in fact accomplish the same thing, just in a different, higher order way? Then when you get into combining fuzzy with known, it's like different organs in the brain combining to serve different functions. When I know a rule and recall it, I believe it to be true and act immediately on it. When I'm not sure, I get fuzzy and try to deduce it. The more data and inputs I have about a given environmental condition, problem, subject, input, fact, etc., the easier it becomes to "reason" using fuzzy links to try to work out the answer. Unless I get information overload or the complexity exceeds one human brain's capability. I've always felt that techniques are complementary and probably we employ multiple subsystems in our brains together to act like humans. [1] https://en.m.wikipedia.org/wiki/CLIPS https://en.m.wikipedia.org/wiki/CLIPS