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Multidisciplinary Trends in Modern Artificial Intelligence: Turing’s Way

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Artificial Intelligence, Evolutionary Computing and Metaheuristics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 427))

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Abstract

The paper faces the challenge to generalize existing trends and approaches in the field of artificial intelligence. Under consideration are expert systems, dynamic neural networks, probabilistic reasoning, fuzzy logic, genetic algorithms, multi-agent systems, bio-inspired algorithms, distributed nonlinear computing, chaos-driven pattern recognition. Each approach strengths and limitations are stated without exhaustive treatment to involve specialist from adjacent fields in discussion. The most perspective research directions are revealed and analyzed in reference to Turing’s way in artificial intelligence and beyond.

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Authors and Affiliations

  1. Faculty of Computer Science, St. Petersburg State Polytechnical University, Russia, 194021, St. Petersburg, Politechnicheskaya 21

    Elena N. Benderskaya

  2. Graduate School of Management, St. Petersburg State University, Russia, 199004, St. Petersburg, Volkhovsky Per. 3

    Sofya V. Zhukova

Authors
  1. Elena N. Benderskaya
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  2. Sofya V. Zhukova
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Correspondence to Elena N. Benderskaya .

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Editors and Affiliations

  1. , Mathematics and Scientific Computing, National Physical Laboratory, Hampton Road, Teddington, TW11 0LW, United Kingdom

    Xin-She Yang

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Benderskaya, E.N., Zhukova, S.V. (2013). Multidisciplinary Trends in Modern Artificial Intelligence: Turing’s Way. In: Yang, XS. (eds) Artificial Intelligence, Evolutionary Computing and Metaheuristics. Studies in Computational Intelligence, vol 427. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29694-9_13

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  • DOI: https://doi.org/10.1007/978-3-642-29694-9_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29693-2

  • Online ISBN: 978-3-642-29694-9

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