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Channel Selection and Power Control for D2D Communication via Online Reinforcement Learning

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D2D A2C Code Repo

Read/download the finished thesis here

Channel Selection and Power Control for D2D Communication via Online Reinforcement Learning implementations

Individiual actor critic implementation - IAC.py

Multi-headed individiual actor critic implementation - MHIAC.py

Centralized COMA implementation - coma_centralized.py

Partially Centralized COMA implementation - coma_partially_centralized.py

Dual-Critic Implementation - dual_critic.py

Partially Centralized Dual-Critic Implementation - dual_critic_partially_centralized.py

NOTE: Some TRFL files were edited for this work. These files will need to be replaced with the edited files (of the same name) which are available here base_ops.py, discrete_policy_gradient_ops.py

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Channel Selection and Power Control for D2D Communication via Online Reinforcement Learning

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