Bøger af Reinhard Kahle

In this two-volume compilation of articles, leading researchers reevaluate the success of Hilbert's axiomatic method, which not only laid the foundations for our understanding of modern mathematics, but also found applications in physics, computer science and elsewhere.The title takes its name from David Hilbert's seminal talk Axiomatisches Denken, given at a meeting of the Swiss Mathematical Society in Zurich in 1917. This marked the beginning of Hilbert's return to his foundational studies, which ultimately resulted in the establishment of proof theory as a new branch in the emerging field of mathematical logic. Hilbert also used the opportunity to bring Paul Bernays back to Gottingen as his main collaborator in foundational studies in the years to come.The contributions are addressed to mathematical and philosophical logicians, but also to philosophers of science as well as physicists and computer scientists with an interest in foundations.Chapter 8 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Proof theory has long been established as a basic discipline of mathematical logic. It has recently become increasingly relevant to computer science. The - ductive apparatus provided by proof theory has proved useful for metatheoretical purposes as well as for practical applications. Thus it seemed to us most natural to bring researchers together to assess both the role proof theory already plays in computer science and the role it might play in the future. The form of a Dagstuhl seminar is most suitable for purposes like this, as Schlo Dagstuhl provides a very convenient and stimulating environment to - scuss new ideas and developments. To accompany the conference with a proc- dings volume appeared to us equally appropriate. Such a volume not only ?xes basic results of the subject and makes them available to a broader audience, but also signals to the scienti?c community that Proof Theory in Computer Science (PTCS) is a major research branch within the wider ?eld of logic in computer science.

Künstliche Intelligenz ist eine Schlüsseltechnologie, mit der sowohl in der Wissenschaft als auch in der Industrie große Erwartungen verbunden sind. In diesem Buch werden sowohl die Perspektiven als auch die Grenzen dieser Technologie diskutiert. Das betrifft die praktischen, theoretischen und konzeptionellen Herausforderungen, denen sich die KI stellen muss. In einer Frühphase standen in der KI Expertensysteme im Vordergrund, bei denen mit Hilfe symbolischer Datenverarbeitung regelbasiertes Wissen verarbeitet wurde. Heute wird die KI von statistik-basierten Methoden im Bereich des maschinellen Lernens beherrscht. Diese subsymbolische KI wird an den Lehren, die aus der Frühphase der KI gezogen werden können, gemessen. Als Ergebnis wird vor allem für eine hybride KI argumentiert, die die Potentiale beider Ansätze zur Entfaltung bringen kann.