rule-based

Overview of the AI systems

All the systems we have examined so far, including deep learning, can in essence be traced back to two methods: the rule-based method and the corpus-based method. This also applies to the systems we have not discussed to date, namely simple automata and hybrid systems, which combine the two above approaches. If we integrate these variants, we will arrive at the following overview: A: Rule-based systems Rule-based systems are based on calculation rules. These rules are invariably IF-THEN commands, i.e. instructions which assign a certain result to a certain input. These systems are always deterministic, i.e. a certain input always

By Hans Rudolf Straub|2025-11-12T10:58:42+00:005. May 2020|Categories: Artificial Intelligence|Tags: Artificial Intelligence, corpus-based, Intelligence, neural network, rule-based, search engine|0 Comments

Rule-based AI: Where is the intelligence situated

Two AI variants: rule-based and corpus-based The two AI variants mentioned in previous blog posts are still topical today, and they have registered some remarkable successes. The two differ from each other not least in where precisely their intelligence is situated. Let’s first have a look at the rule-based system. Structure of a rule-based system In the Semfinder company, we used a rule-based system. I drew the following sketch of it in 1999: Green: data Yellow: software Light blue: knowledge ware Dark blue: knowledge engineer The sketch consists of two rectangles, which represent different locations. The rectangle bottom left shows

By Hans Rudolf Straub|2025-11-12T11:02:54+00:0016. April 2020|Categories: Artificial Intelligence|Tags: Artificial Intelligence, Intelligence, Knowledge base, rule-based|0 Comments

The three innovations of rule-based AI

Have the neural networks outpaced the rule-based systems? It cannot be ignored: corpus-based AI has overtaken rule-based AI by far. Neural networks are making the running wherever we look. Is the competition dozing? Or are rule-based systems simply incapable of yielding equivalent results to those of neural networks? My answer is that both methods are predisposed for performing very different functions as a matter of principle. A look at their respective modes of action makes clear what the two methods can usefully be employed for. Depending on the problem to be tackled, one or the other has an advantage. Yet

By Hans Rudolf Straub|2025-11-12T11:05:45+00:0030. March 2020|Categories: Artificial Intelligence|Tags: Artificial Intelligence, concept, Concept architecture, rule-based, semantics|0 Comments

Specification of the challenges for rule-based AI

Rule-based AI is lagging behind The distinction between rule-based AI and corpus-based AI makes sense in several respects since the two systems work in completely different ways. This does not only mean that their challenges are completely different, it also means that as a consequence, their development trajectories are not parallel in terms of time. In my view, the only reason for this is that rule-based AI has reached a dead end from which it will only be able to extricate itself once it has correctly identified its challenges. This is why these challenges will be described in more detail below.

By Hans Rudolf Straub|2025-11-12T11:06:22+00:0030. March 2020|Categories: Artificial Intelligence|Tags: Artificial Intelligence, rule-based|0 Comments

AI: Vodka and tanks

AI in the last century AI is a big buzzword today but was already of interest to me in my field of natural language processing in the 1980s and 1990s. At that time, there were two methods which were occasionally labelled AI, but they could not have been more different from each other. The exciting thing is that these two different methods still exist today and continue to be essentially different from each other. AI-1: vodka The first method, i.e. the one already used by the very first computer pioneers, was purely algorithmic, i.e. rule-based. Aristotle’s syllogisms are a paradigm of this type