5

First of all, I would like to point out the main differences between knowledge base and (Deep) machine learning, specially when the main focus is on "AI" not "Data Science": NNs are like a black box; Even if they learn a dataset and gain the power of generalization over the problem domain, you'd never know how they are working. if you scrutinize the details ...


5

The key feature of an expert system is that the knowledge base is structured to be traversed by the inference engine. Web sites like Stack Exchange don't really use an inference engine; they do full-text searches on minimally-structured data. A real inference engine would be able to answer novel queries by putting together answers to existing questions; ...


4

No, I don't think there's any reason to say that - in general - CRUD apps "are" expert systems. A given CRUD app could incorporate an expert system, but by and large CRUD apps are considered among the "dumbest" of applications exactly because they don't feature much intelligence... you can just Create, Read, Update and Delete entities. From what I've seen, ...


3

Sure! There's the whole Semantic Web scene! OWL is derived from DLs and Frames, arguably has a lot in common with semantic networks too. Expert-driven decision support systems are still being developed (and researched) in industries where the human is required to take responsibility or getting data is not going to happen. As the ideas evolve so do the names. ...


3

Oh yeah, definitely. Just to pick one example, you have Douglas Hofstader's group at Indiana. I think most of what they do would fall under the rubric of GOFAI (or at least closer to that than the statistical machine learning stuff). Beyond that, just go to the CORR and browse around the AI category. You'll see plenty of neural networks and ...


3

Although asked over 3 years ago, the question is still interesting and while I agree with the original answer, a lot can be added to it. First, I'd like to point out that the term "knowledge base" is very ambiguous and it means different things to different people. For example, there is no sharp distinction between knowledge base and neural network....


2

We cannot do homework for students in this network, however I can suggest that several items affecting cost and several usage patterns are missing and the number of rules is shy by an order of magnitude. I wholeheartedly agree with the educational directives you received. Consider first developing your lists further to include peripherals like DVD burner, ...


2

I would say Expert Systems is still being taught. For instance, if you look at some of the open courses like MIT's, there are still lectures on it. Also, looking at the CLIPS documentation, you will find a couple of examples of usage from 2005. What I suspect is that Expert Systems are now embedded with "normal systems" in practice. Hence it may be ...


1

A recent research example is the "Grind" system. Take a look at the paper Computing FO-Rewritings in $\mathcal{E} \mathcal{L}$ in Practice: from Atomic to Conjunctive Queries (2018) by Peter Hansen and Carsten Lutz. Here's the abstract. A prominent approach to implementing ontology-mediated queries (OMQs) is to rewrite into a first-order query, ...


1

Are there companies that still use expert systems? There are still some expert system inference engines available in open source form, in particular CLIPS rules A specialization of your question could be: what companies are using CLIPS in 2020 ? I don't have any ideas, even if I did try in https://github.com/bstarynk/clips-rules-gcc And the RefPerSys ...


1

TL;DR: What makes AI is not if-then statements, but rather the automated reasoning that went into selecting those particular if-then statements. You're focusing on the structure of the output rather than how the output was produced. Having if-then control flow statements is not sufficient to make a program "AI". AI aims to enable machines to solve ...


1

Welcome to the AI stack Jake. This probably isn't going to be possible. Modern Psudo-random number generators, like Mersenne Twister, are designed not to have any patterns in them, so there's nothing to learn from. You could however, try something like predicting the values of a broken random number generator, like RANDU. These aren't used anymore, ...


1

CRUD applications today can't be considered expert systems. However, even the so-called expert systems, which are currently developed, are implemented using normal programming statements, but what is important is the architecture that is built. Current expert systems use only if-then types of rules, which produce data results that can be used as inputs to ...


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