> I suspect that the next big AI breakthrough will result at least in part from constraining LLM decisions with old AI approaches.
> Going beyond that, I wonder if an agent could keep a running list of assumptions & known facts (with confidence levels/intervals), test them (actively & passively), update them when observations contradict them, and act based on them
I don’t think that’s “going beyond that”. It’s a blackboard system from the 1980s (https://en.wikipedia.org/wiki/Blackboard_system)
Didn't old-school blackboard systems sort of evaporate into a modern combination of a persistence layer, a task queue, pub-sub, and bespoke code for evaluating/scheduling/executing tasks?
That's not really what I was referring to. I meant more of a system of working assumptions (call them first-class axioms, propositions, facts, whatever) that govern behavior and can be updated when observations occur that contradict them -- not a task queue or a database of all known facts. Sort of like human core beliefs that dictate how we see the world.