/Research-Topic-2

Improving Reliability by Risk-Averse Reinforcement Learning over Sub6GHz/mmWave Integrated Networks

Primary LanguagePython

Implementation of Improving Reliability by Risk-Averse Reinforcement Learning over Sub6GHz/mmWave Integrated Networks

by Thi Ha Ly Dinh∗ , Megumi Kaneko∗ , Kenichi Kawamura† , Takatsune Moriyama† , Yasushi Takatori†

Discription: This is a implementation of the paper using Python.

Credits and reference

[1] Dinh, T. H. L., Kaneko, M., Kawamura, K., Moriyama, T., & Takatori, Y. (2022). Improving Reliability by Risk-Averse Reinforcement Learning over Sub6GHz/mmWave Integrated Networks. ICC 2022 - IEEE International Conference on Communications. https://doi.org/10.1109/icc45855.2022.9839175