3 ms·
Expert systems tend not to scale very well. Once you get beyond $some_threshold rules, the decision algorithms get slow and the rules start conflicting with eac
by dreamcompiler 4y ago
Expert systems tend not to scale very well. Once you get beyond $some_threshold rules, the decision algorithms get slow and the rules start conflicting with each other. What's needed is a meta-rule system that works during the knowledge capture phase to keep the rule set consistent.
Lots of work was done on this problem in the late 80s/early 90s but I don't know what the current SOTA is since expert systems fell out of fashion. I'd expect it to be fairly straightforward to maintain a consistent rule base with modern computers that are 1000x bigger and faster than those of the 80s.
- AnimalMuppet 4y ago> I'd expect it to be fairly straightforward to maintain a consistent rule base with modern computers that are 1000x bigger and faster than those of the 80s. Maybe not. Maybe they'll just be used to create a rule base that is 1000x bigger than those of the 80s, and you'll still have trouble maintaining consistency.
- mark_l_watson 4y agoThe Rete algorithm used in OPS5 scales as O(N) where N is the number of rules - which is good. However, it scales as O(D^2) where D is the number of working memory facts.