Towards Explainable Reinforcement Learning in Optical Networks: The RMSA Use Case
Paper in proceeding, 2024
We propose an approach to extract explanations from a trained reinforcement learning agent. Our analysis over three RMSA environment variations shows how the agent uses the input information, increasing our understanding of its learned policy.
Routing, modulation format, and spectrum assignment
Reinforcement learning
Explainable AI
Author
Omran Ayoub
University of Applied Sciences and Arts of Southern Switzerland
Carlos Natalino Da Silva
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Paolo Monti
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Conference on Optical Fiber Communication, Technical Digest Series
W4I.6
9781957171326 (ISBN)
Optical Fiber Communications Conference and Exhibition (OFC)
San Diego, CA, USA,
San Diego, CA, USA,
Photonic-Assisted Hardware for Reservoir Computing (BRAIN)
Swedish Research Council (VR) (2022-04798), 2023-01-01 -- 2026-12-31.
Areas of Advance
Information and Communication Technology
Subject Categories
Telecommunications
Communication Systems
Computer Science
DOI
10.1364/OFC.2024.W4I.6