A Conceptual Approach to Multi-Model Adaptive Systems

• Author(s): Aadesh Vishwasrao Deokar; Ajit Vaijinath Kumbhar; Sarthak Santosh Patange; Samrat Dnyaneshwar Prakshale; Manisha Anjikhane
• Paper ID: 1715455
• Page: 1872-1874
• Published Date: 23-03-2026
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 9 March-2026
• 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.

Citations

IRE Journals:
Aadesh Vishwasrao Deokar, Ajit Vaijinath Kumbhar, Sarthak Santosh Patange, Samrat Dnyaneshwar Prakshale, Manisha Anjikhane "A Conceptual Approach to Multi-Model Adaptive Systems" Iconic Research And Engineering Journals Volume 9 Issue 9 2026 Page 1872-1874 https://doi.org/10.64388/IREV9I9-1715455

IEEE:
Aadesh Vishwasrao Deokar, Ajit Vaijinath Kumbhar, Sarthak Santosh Patange, Samrat Dnyaneshwar Prakshale, Manisha Anjikhane "A Conceptual Approach to Multi-Model Adaptive Systems" Iconic Research And Engineering Journals, vol. 9, no. 9, Mar. 2026, doi: https://doi.org/10.64388/IREV9I9-1715455

APA:
Aadesh Vishwasrao Deokar, Ajit Vaijinath Kumbhar, Sarthak Santosh Patange, Samrat Dnyaneshwar Prakshale, Manisha Anjikhane (2026). A Conceptual Approach to Multi-Model Adaptive Systems. Iconic Research And Engineering Journals, 9(9). doi: https://doi.org/10.64388/IREV9I9-1715455

MLA:
Aadesh Vishwasrao Deokar, Ajit Vaijinath Kumbhar, Sarthak Santosh Patange, Samrat Dnyaneshwar Prakshale, Manisha Anjikhane "A Conceptual Approach to Multi-Model Adaptive Systems" Iconic Research And Engineering Journals, vol. 9, no. 9, Mar. 2026. Crossref, https://doi.org/10.64388/IREV9I9-1715455

BibTeX

@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}
}