Designing ML-Enabled Software Systems with ML Model Composition: A Green AI Perspective

The adoption of Machine Learning (ML) in the past few decades has revolutionized the implementation of traditional software systems, although the concept of ML dates back to the 1950s [2], [17]. ML models do not work in isolation, but are mostly used as parts of larger software systems [8], which are referred to as ML systems or ML-enabled systems [14].

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Published
2025-04-27
DOI
https://doi.org/10.1109/cain66642.2025.00040
Primary Topic
Multi-Agent Systems and Negotiation
Type
article
Field-Weighted Citation Impact
0.00

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article

Designing ML-Enabled Software Systems with ML Model Composition: A Green AI Perspective

Rumbidzai Chitakunye
Multi-Agent Systems and Negotiation
article

Designing ML-Enabled Software Systems with ML Model Composition: A Green AI Perspective

Rumbidzai Chitakunye
article en

Abstract

The adoption of Machine Learning (ML) in the past few decades has revolutionized the implementation of traditional software systems, although the concept of ML dates back to the 1950s [2], [17]. ML models do not work in isolation, but are mostly used as parts of larger software systems [8], which are referred to as ML systems or ML-enabled systems [14].

Vrije Universiteit Amsterdam (NL)
H2020 Marie Skłodowska-Curie Actions
Openalex Percentile: Top 93%
Multi-Agent Systems and Negotiation
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Designing ML-Enabled Software Systems with ML Model Composition: A Green AI Perspective — Rumbidzai Chitakunye · (2025) | TGRS Research Map | TGRS