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

The coupling of quantum computing with multi-agent reinforcement learning (MARL) provides an exciting direction to tackle intricate decision-making tasks in high-dimensional spaces. This work introduces a new quantum-inspired multi-agent reinforcement learning (QiMARL) model, utilizing quantum paral...

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Principais autores: Sapthak Mohajon Turjya, Anjan Bandyopadhyay, M. Shamim Kaiser, Kanad Ray
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2025-09-01
Serier:AI
Fag:
energy distribution
nodal power stations
quantum computing
MAB
QiMARL
Online adgang:https://www.mdpi.com/2673-2688/6/9/209
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