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by IQAC KIITKIIT Deemed to be University — Internal Quality Assurance Cell

Publication2025

QiMARL: Quantum-Inspired Multi-Agent Reinforcement Learning Strategy for Efficient Resource Energy Distribution in Nodal Power Stations

The record

Type
Publication
Date
1 September 2025
Level
International — held abroad
Journal
AI Switzerland
Volume
6
Issue
9
Published
1 September 2025
DOI
10.3390/ai6090209
Scopus ID
105017140429
ISSN
26732688
Authors
4
Open access
Yes
Citations
6
International co-authorship
Yes
Co-author countries
BD, IN

Classification

Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.

UN Sustainable Development Goals

  1. 7.2 Substantially increase the share of renewable energy in the global energy mix

    TargetPrimaryHigh confidenceJudged

    Quantum-inspired reinforcement learning optimizes multi-agent energy distribution in hybrid power stations, improving grid efficiency and renewable energy integration scalability.

    High confidence
    The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
    Judged
    Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

  2. 17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing

    TargetSecondaryHigh confidenceRule-derivedrule sdg17-structural-v1

    Structural signal: co-authorship outside India.

    Rule-derived
    Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
    Produced by
    sdg17-structural-v1, under kortex-publication-v1

Viksit Bharat @2047

  1. vb-2.5 Green economy, energy transition and climate resilience

    Sub-themePrimaryHigh confidenceJudged

    Advanced AI optimization for renewable energy distribution directly supports clean energy transition and climate-resilient power infrastructure.

    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

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KIIT Deemed to be University. “QiMARL: Quantum-Inspired Multi-Agent Reinforcement Learning Strategy for Efficient Resource Energy Distribution in Nodal Power Stations”. Kortex.

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