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Lambda Computatrix (LC)—Towards a Computational Enhanced Understanding of Production and Management

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Proceedings of Sixth International Congress on Information and Communication Technology

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 236))

Abstract

This paper describes why and how the Artificial Intelligence (AI) discipline will affect decisions and what is the difference to decisions in the past, focusing on the application to industrial production. From this analysis with a global economic systemic towards universal model, there will be given a globally emerging company structures outlook, concerning their decision situation, and way how to decide in future rightly. For this purpose, universal logical tools, that implement the lambda calculus for quantification logic may be useful. We define these as Lambda Computatrix (LC). Examples are Theorem Provers (TP) like Isabelle or Lambda-Prolog. They help to decide precisely to reach company, societal and environmental goals. The key issue of the LC is the universal approach of computation, which is connecting graph-theoretically potentially every node with each other one by a communication edge. LC hence enables increasingly intelligent communication, informationally and materially in terms of logistics and production processes.

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Author information

Authors and Affiliations

  1. Carinthia University of Applied Sciences, 9524, Villach, Austria

    Bernhard Heiden, Erich Hartlieb & Denise Foro-Szasz

  2. University of Graz, 8010, Graz, Austria

    Bernhard Heiden & Bianca Tonino-Heiden

  3. National Technical University ‘Kharkiv Polytechnic Institute’, 61002, Kharkiv, Ukraine

    Volodymyr Alieksieiev

Authors
  1. Bernhard Heiden
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  2. Bianca Tonino-Heiden
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  3. Volodymyr Alieksieiev
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  4. Erich Hartlieb
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  5. Denise Foro-Szasz
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Corresponding author

Correspondence to Bernhard Heiden .

Editor information

Editors and Affiliations

  1. Middlesex University, London, UK

    Xin-She Yang

  2. University of Reading, Reading, UK

    Simon Sherratt

  3. JIS University, Kolkata, India

    Nilanjan Dey

  4. Global Knowledge Research Foundation, Ahmedabad, India

    Amit Joshi

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Heiden, B., Tonino-Heiden, B., Alieksieiev, V., Hartlieb, E., Foro-Szasz, D. (2022). Lambda Computatrix (LC)—Towards a Computational Enhanced Understanding of Production and Management. In: Yang, XS., Sherratt, S., Dey, N., Joshi, A. (eds) Proceedings of Sixth International Congress on Information and Communication Technology. Lecture Notes in Networks and Systems, vol 236. Springer, Singapore. https://doi.org/10.1007/978-981-16-2380-6_4

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