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Exploring the Design Space for Myopia-Avoiding Distributed Control Systems Using a Classification Model

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 694))

Abstract

Avoiding myopia, suboptimal behaviour, caused by the limited information horizon and computation capacity of agents, has been recognized as a major design challenge for the future academic development and industrial adoption of distributed production control systems. In [3] existing literature from various research streams has been reviewed to classify design decisions that can be made to avoid myopic decision making. In the present paper, this model will be validated by mapping different paradigms of distributed control onto it. Through this exercise, an initial validation of the proposed classification model can be attained and a starting point for a classification of existing distributed production control approaches based on design features is provided. This will help designers of distributed architectures in production control to better understand their design space, take deliberate steps towards the avoidance of myopic behaviour, and identify unexplored areas within the design space.

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Correspondence to Tianyi Wang .

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Wang, T., Blunck, H., Bendul, J. (2017). Exploring the Design Space for Myopia-Avoiding Distributed Control Systems Using a Classification Model. In: Borangiu, T., Trentesaux, D., Thomas, A., Leitão, P., Oliveira, J. (eds) Service Orientation in Holonic and Multi-Agent Manufacturing . SOHOMA 2016. Studies in Computational Intelligence, vol 694. Springer, Cham. https://doi.org/10.1007/978-3-319-51100-9_26

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  • DOI: https://doi.org/10.1007/978-3-319-51100-9_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51099-6

  • Online ISBN: 978-3-319-51100-9

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