Modeling Machine Learning Concerns in Collective Adaptive Systems

Petr Hnětynka, Martin Kruliš, Michal Töpfer, Tomáš Bureš

2023

Abstract

Collective adaptive systems (CAS) are systems composed of a large number of heterogeneous entities without central control that adapt their behavior to reach a common goal. Adaptation and collaboration in such systems are traditionally specified via a set of logical rules. Nevertheless, such rules are often too rigid and do not allow for the evolution of a system. Thus, recent approaches started with the introduction of machine learning (ML) methods into CAS. In the is paper, we present a model-driven approach showing how CAS, which employs ML methods for adaptation, can be modeled—on both the platform independent and specific levels. In particular, we define a meta-model for modeling CAS and a mapping of concepts defined in the meta-model to the Python framework.

Paper Citation

in Harvard Style

Hnětynka P., Kruliš M., Töpfer M. and Bureš T. (2023). Modeling Machine Learning Concerns in Collective Adaptive Systems. In Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering - Volume 1: MODELSWARD, ISBN 978-989-758-633-0, pages 55-62. DOI: 10.5220/0011693300003402

in Bibtex Style

@conference{modelsward23,
author={Petr Hnětynka and Martin Kruliš and Michal Töpfer and Tomáš Bureš},
title={Modeling Machine Learning Concerns in Collective Adaptive Systems},
booktitle={Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering - Volume 1: MODELSWARD,},
year={2023},
pages={55-62},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011693300003402},
isbn={978-989-758-633-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering - Volume 1: MODELSWARD,
TI - Modeling Machine Learning Concerns in Collective Adaptive Systems
SN - 978-989-758-633-0
AU - Hnětynka P.
AU - Kruliš M.
AU - Töpfer M.
AU - Bureš T.
PY - 2023
SP - 55
EP - 62
DO - 10.5220/0011693300003402