Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology

Robustification of Self-Optimising Systems via Explicit Treatment of Uncertain Information

Authors
Jan H. Schoenke, Werner Brockmann
Corresponding Author
Jan H. Schoenke
Available Online June 2015.
DOI
https://doi.org/10.2991/ifsa-eusflat-15.2015.25How to use a DOI?
Keywords
Self-Optimising Systems, Uncertain Information, Uncertainty Treatment, Regression
Abstract
Uncertainty treatment in self-optimising systems touches two design-issues. Firstly, a valid estimation of uncertainties within the system is impossible beforehand as the uncertainties as well as the systems behaviour changes during run-time due to self-optimisation. Secondly, the design of a selfoptimising system needs to mediate between the often conflicting goals of optimality and robustness. Here we present the concept for a lightweight algorithmic add-on for self-optimising function approximators that enables to reflect uncertainties related to the current state and to flexibly combine optimality and robustness in one design. Illustrating examples of TS-fuzzy systems highlight the properties of our approach.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Jan H. Schoenke
AU  - Werner Brockmann
PY  - 2015/06
DA  - 2015/06
TI  - Robustification of Self-Optimising Systems via Explicit Treatment of Uncertain Information
BT  - 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (IFSA-EUSFLAT-15)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.25
DO  - https://doi.org/10.2991/ifsa-eusflat-15.2015.25
ID  - Schoenke2015/06
ER  -