Learning of Consistent Preference Relations for Decision Making and Optimization in Context of Interacting Goals

DOI

10.2991/asum.k.210827.036How to use a DOI?

Keywords

Learning of preference relations, Fuzzy interactions between decision goals, Real-world optimization problem, Resource planning, Conflicting goals, Reinforcement-based optimization

Abstract

In former papers a decision and optimization algorithm based on interactions between goals was introduced and it was shown how it solves relevant real-world problems. However, the algorithm assumed preference information on the goals as initially given. In this paper we describe a learning algorithm that derives such preference information from decision and optimization input data. It is shown how the former algorithm is improved and how this improvement links the algorithm to reinforcement-based machine learning optimization.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Rudolf Felix
PY  - 2021
DA  - 2021/08/30
TI  - Learning of Consistent Preference Relations for Decision Making and Optimization in Context of Interacting Goals
BT  - Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)
PB  - Atlantis Press
SP  - 266
EP  - 273
SN  - 2589-6644
UR  - https://doi.org/10.2991/asum.k.210827.036
DO  - 10.2991/asum.k.210827.036
ID  - Felix2021
ER  -