Editing Expert system (section)

=== Current approaches to expert systems ===
The limits of prior type of expert systems prompted researchers to develop new types of approaches. They have developed more efficient, flexible, and powerful methods to simulate the human decision-making process. Some of the approaches that researchers have developed are based on new methods of artificial intelligence (AI), and in particular in [[machine learning]] and [[data mining]] approaches with a feedback mechanism.<ref>{{Cite journal |last1=Chung |first1=Junyoung |last2=Gulcehre |first2=Caglar |last3=Cho |first3=Kyunghyun |last4=Bengio |first4=Yoshua |date=2015-06-01 |title=Gated Feedback Recurrent Neural Networks |url=http://proceedings.mlr.press/v37/chung15.html |journal=International Conference on Machine Learning |language=en |publisher=PMLR |pages=2067–2075 |arxiv=1502.02367}}</ref>{{failed verification|reason=The article doesn't mention expert systems at all.|date=May 2024}} [[Recurrent neural network]]s often take advantage of such mechanisms. Related is the discussion on the disadvantages section.

Modern systems can incorporate new knowledge more easily and thus update themselves easily. Such systems can generalize from existing knowledge better and deal with vast amounts of complex data. Related is the subject of [[big data]] here. Sometimes these type of expert systems are called "intelligent systems."<ref name="CADsurvey"/>

More recently, it can be argued that expert systems have moved into the area of [[business rule]]s and [[business rules management system]]s.