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Towards Massive Distribution of Intelligence for 6G Network Management using Double Deep Q-Networks
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  • Sayantini Majumdar ,
  • Susanna Schwarzmann ,
  • Riccardo Trivisonno ,
  • Georg Carle
Sayantini Majumdar
Huawei Technologies & Technical University of Munich, Huawei Technologies & Technical University of Munich

Corresponding Author:[email protected]

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Susanna Schwarzmann
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Riccardo Trivisonno
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Georg Carle
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Abstract

Our solution evaluation is based on synthetic data-sets generated by our internally-developed simulation platform. This means we do not use any stand-alone, external or internal data-sets. Our platform code is not public, but we describe in detail the design of the platform and the data-set generator module, for other researchers to reproduce our results. The code is written in 100% Python, leveraging object-oriented approaches for code reusability.
2023Published in IEEE Transactions on Network and Service Management on pages 1-1. 10.1109/TNSM.2023.3333875