The new AI is general and mathematically rigorous

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1 Scopus citations


Most traditional artificial intelligence (AI) systems of the past decades are either very limited, or based on heuristics, or both. The new millennium, however, has brought substantial progress in the field of theoretically optimal and practically feasible algorithms for prediction, search, inductive inference based on Occam's razor, problem solving, decision making, and reinforcement learning in environments of a very general type. Since inductive inference is at the heart of all inductive sciences, some of the results are relevant not only for AI and computer science but also for physics, provoking nontraditional predictions based on Zuse's thesis of the computer-generated universe. We first briefly review the history of AI since Gödel's 1931 paper, then discuss recent post-2000 approaches that are currently transforming general AI research into a formal science. © 2010 Higher Education Press and Springer-Verlag Berlin Heidelberg.
Original languageEnglish (US)
Pages (from-to)347-362
Number of pages16
JournalFrontiers of Electrical and Electronic Engineering in China
Issue number3
StatePublished - Jul 27 2010
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2022-09-14

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering


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