Abstract
Against the background of knowledge-based systems, Turing’s famous question, which moved early AI researchers, can be taken up again: Can these systems “think”? Are they “intelligent”? The analysis shows that knowledge-based expert systems as well as conventional computer programs are based on algorithms. Even the separation of knowledge base and problem solving strategy does not change this, because both components of an expert system must be represented in algorithmic data structures in order to finally become programmable on a computer.
This also applies to the realization of natural language through computers. One example is J. Weizenbaum’s ELIZA language program. As a human expert, ELIZA will simulate a psychiatrist talking to a patient. These are rules on how to react to certain sentence patterns of the patient with certain sentence patterns of the “psychiatrist”. In general, it is about the recognition or classification of rules with regard to their applicability in situations. In the simplest case, the equality of two symbol structures must be determined, as determined by the EQUAL function in the LISP programming language for symbol lists. An extension exists if terms and variables are included in the symbolic expressions, e.g.
(x B C)
(A B y)
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Mainzer, K. (2020). Computers Learn to Speak. In: Artificial intelligence - When do machines take over?. Technik im Fokus. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-59717-0_5
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