WFRF:(Silva Natalino)
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- Ayoub, Omran (author)
Towards Explainable Reinforcement Learning in Optical Networks: The RMSA Use Case
- Article/chapterEnglish2024
Publisher, publication year, extent ...
- 2024
- electronicrdacarrier
Numbers
- LIBRIS-ID:oai:research.chalmers.se:363812cc-150c-41af-b5d8-ceab9434b1f1
- https://research.chalmers.se/publication/540626URI
- https://doi.org/10.1364/OFC.2024.W4I.6DOI
Supplementary language notes
- Language:English
- Summary in:English
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- SwePubSwePub
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Notes
- 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.
Subject headings and genre
- TEKNIK OCH TEKNOLOGIER Elektroteknik och elektronik Telekommunikation hsv//swe
- ENGINEERING AND TECHNOLOGY Electrical Engineering, Electronic Engineering, Information Engineering Telecommunications hsv//eng
- TEKNIK OCH TEKNOLOGIER Elektroteknik och elektronik Kommunikationssystem hsv//swe
- ENGINEERING AND TECHNOLOGY Electrical Engineering, Electronic Engineering, Information Engineering Communication Systems hsv//eng
- NATURVETENSKAP Data- och informationsvetenskap Datavetenskap hsv//swe
- NATURAL SCIENCES Computer and Information Sciences Computer Sciences hsv//eng
- Reinforcement learning
- Explainable AI
- Routing, modulation format, and spectrum assignment
Added entries (persons, corporate bodies, meetings, titles ...)
- Natalino Da Silva, Carlos,1987Chalmers tekniska högskola,Chalmers University of Technology(Swepub:cth)carda (author)
- Monti, Paolo,1973Chalmers tekniska högskola,Chalmers University of Technology(Swepub:cth)mpaolo (author)
- Chalmers tekniska högskola (creator_code:org_t)
Related titles
- In:Conference on Optical Fiber Communication, Technical Digest Series
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