A blockchain-integrated, energy-efficient dual-agent reinforcement learning framework for resilient electric vehicles

This paper introduces an energy-efficient, Blockchain-Based, Dual-Agent, Reinforcement Learning (BDARL) model of resilient EV-grid integrative effect. All EV energy transactions and agent decisions are validated by the blockchain layer that is integrated through a lightweight proof-of-stake consensu...

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Detalles Bibliográficos

Principais autores:	Jagdish R. Yadav, Asha Durafe, P Anitha, Ch.Phani Kumar, Reddi Khasim Shaik, Gutti Yateesh
Formato:	Artigo
Idioma:	Inglês
Publicado:	Elsevier 2026-04-01
Series:	Ain Shams Engineering Journal
Assuntos:	Blockchain Reinforcement learning Electric vehicles Dual-agent systems Cybersecurity Smart charging
Acceso en liña:	http://www.sciencedirect.com/science/article/pii/S2090447926001103
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