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Symbolic Artificial Intelligence and Numeric Artificial Neural Networks: Towards a Resolution of the Dichotomy

  • Vasant Honavar
Part of the The Springer International Series In Engineering and Computer Science book series (SECS, volume 292)

Abstract

The attempt to understand intelligence entails building theories and models of brains and minds, both natural as well as artificial. From the earliest writings of India and Greece, this has been a central problem in philosophy. The advent of the digital computer in the 1950’s made this a central concern of computer scientists as well (Turing, 1950). The parallel development of the theory of computation (by John von Neumann, Alan Turing, EmilPost, Alonzo Church, Charles Kleene, Markov and others) provided a new set of tools with which to approach this problem — through analysis, design, and evaluation of computers and programs that exhibit aspects of intelligent behavior — such as the ability to recognize and classify patterns; to reason from premises to logical conclusions; and to learn from experience.

Keywords

Neural Network Artificial Intelligence Intelligent System Turing Machine Computational Architecture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 1995

Authors and Affiliations

  • Vasant Honavar
    • 1
  1. 1.Department of Computer ScienceIowa State UniversityAmes

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