I know that
In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert.
Does the architecture of an expert system same as that of knowledge based system or is there any difference?
What are the stages in development of expert system?
As far as I know, experts systems were popular around the 80s-90s, before the big trend of Machine Learning. They were mostly based on symbolic logic reasoning, as opposed to statistics in ML.
They can probably be considered as one the first stages of ML-based systems: experts systems automate the reasoning steps based on some data, which is a bit similar to ML. However the data was strongly structured (and possibly quite complex) and usually had to be entered manually by an expert. This is the main reason why ML approaches made them obsolete for the most part: ML systems can learn from a vast amount of possibly noisy features with little structure, whereas the cost of preparing the data for experts systems was prohibitive.
Experts systems were indeed a kind of knowledge-based system (probably the first generation), but I think the latter are much more general: knowledge-based system include many different kinds of data base and different methods for processing it.
Note: this answer is based on my general understanding and knowledge of these terms, which is probably correct but not sure ;)
