WA4b.1

A Constrained RL Approach for Cost-Efficient Delivery of Latency-Sensitive Applications

Ozan Aygun, New York University, United States; Vincenzo Norman Vitale, Antonia Tulino, University of Naples Federico II, Italy; Hao Feng, Intel Labs, United States; Elza Erkip, New York University, United States; Jaime Llorca, University of Trento, Italy
Session:
WA4b: Reinforcement Learning for Autonomous Systems Lecture
Track:
Adaptive Systems, Machine Learning, and Data Analytics
Location:
Nautilus
Presentation Time:
Wed, 29 Oct, 10:15 - 10:40 PT (UTC -7)
Presentation
Discussion
Resources
No resources available.
Session WA4b
WA4b.1: A Constrained RL Approach for Cost-Efficient Delivery of Latency-Sensitive Applications
Ozan Aygun, New York University, United States; Vincenzo Norman Vitale, Antonia Tulino, University of Naples Federico II, Italy; Hao Feng, Intel Labs, United States; Elza Erkip, New York University, United States; Jaime Llorca, University of Trento, Italy
WA4b.2: SCoTT: Strategic Chain-of-Thought Tasking for Wireless-Aware Robot Navigation in Digital Twins
Aladin Djuhera, Amin Seffo, Vlad Andrei, Holger Boche, Technical University of Munich, Germany; Walid Saad, Virginia Tech, United States
WA4b.3: Feedback-Assisted Decentralized Q-Learning for Dynamic Spectrum Access
Ghilas Aissou, Salman Habib, Arizona State University, United States; Rémi Chou, The University of Texas at Arlington, United States; Taejoon Kim, Arizona State University, United States
Contacts