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A Conceptual Approach to Multi-Model Adaptive Systems
Subject area: Science,Engineering and Technology · Area of research: Adaptive Systems
DOI: https://doi.org/10.64388/IREV9I9-1715455
Abstract
If you think about how most software systems are built today, they almost always rely on a single underlying model: one that was designed with a particular kind of environment in mind. That works well enough when things stay predictable, but real-world conditions rarely cooperate. This paper puts forward a multi-model hypothesis: the idea that a system becomes genuinely adaptive when it carries several models internally and knows which one to lean on depending on what it's dealing with at any given moment. The result is a system that handles variability more gracefully, without falling apart when assumptions break down. What's presented here is a conceptual starting point. The formal math, experimental testing, and deeper analysis are intentionally left for follow-up work.
Keywords
Adaptive Systems, Dynamic Models, Model Selection, Multi-Model Systems, System Behavior.
How to cite this paper
@article{1715455,
author = {Aadesh Vishwasrao Deokar, Ajit Vaijinath Kumbhar, Sarthak Santosh Patange, Samrat Dnyaneshwar Prakshale, Manisha Anjikhane},
title = {A Conceptual Approach to Multi-Model Adaptive Systems},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {9},
pages = {1872-1874},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1715455.pdf},
abstract = {If you think about how most software systems are built today, they almost always rely on a single underlying model: one that was designed with a particular kind of environment in mind. That works well enough when things stay predictable, but real-world conditions rarely cooperate. This paper puts forward a multi-model hypothesis: the idea that a system becomes genuinely adaptive when it carries several models internally and knows which one to lean on depending on what it's dealing with at any given moment. The result is a system that handles variability more gracefully, without falling apart when assumptions break down. What's presented here is a conceptual starting point. The formal math, experimental testing, and deeper analysis are intentionally left for follow-up work.},
keywords = {Adaptive Systems, Dynamic Models, Model Selection, Multi-Model Systems, System Behavior.},
month = {March},
doi = {https://doi.org/10.64388/IREV9I9-1715455}
}