EVCAR-KG: A Knowledge-Infused Multi-Agent Reinforcement Learning Framework for Resilient Electric Vehicle Charging Network Recovery
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| Format: | Recurso digital |
| Langue: | anglais |
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Zenodo
2025
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| _version_ | 1866902053235720192 |
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| author | Abdelfattah, Mohamed |
| author_facet | Abdelfattah, Mohamed |
| contents | <p>This repository contains the implementation of EVCAR-KG, an ontology-driven knowledge graph framework that enhances multi-agent reinforcement learning for electric vehicle charging network recovery after prolonged power outages.</p> <p>The framework integrates semantic knowledge through an OWL ontology with TD3-MADDPG agents to improve learning efficiency and decision quality during post-outage recovery scenarios. Key features include ontology-based action masking, priority-aware reward shaping, and aggregate representation for scalability.</p> <p>This work was presented at the 36th Forum Bauinformatik 2025 in Aachen, Germany.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15824931 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | EVCAR-KG: A Knowledge-Infused Multi-Agent Reinforcement Learning Framework for Resilient Electric Vehicle Charging Network Recovery Abdelfattah, Mohamed Electric Vehicle Charging Networks Knowledge Graphs Multi-Agent Reinforcement Learning Power Grid Resilience Quality of Service Recovery <p>This repository contains the implementation of EVCAR-KG, an ontology-driven knowledge graph framework that enhances multi-agent reinforcement learning for electric vehicle charging network recovery after prolonged power outages.</p> <p>The framework integrates semantic knowledge through an OWL ontology with TD3-MADDPG agents to improve learning efficiency and decision quality during post-outage recovery scenarios. Key features include ontology-based action masking, priority-aware reward shaping, and aggregate representation for scalability.</p> <p>This work was presented at the 36th Forum Bauinformatik 2025 in Aachen, Germany.</p> |
| title | EVCAR-KG: A Knowledge-Infused Multi-Agent Reinforcement Learning Framework for Resilient Electric Vehicle Charging Network Recovery |
| topic | Electric Vehicle Charging Networks Knowledge Graphs Multi-Agent Reinforcement Learning Power Grid Resilience Quality of Service Recovery |
| url | https://doi.org/10.5281/zenodo.15824931 |