Safe RAN control: A Symbolic Reinforcement Learning Approach
Author:
Affiliation:
1. Ericsson Research,Research Area Artificial Intelligence (AI)
2. University of California
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9831427/9831807/09831850.pdf?arnumber=9831850
Reference27 articles.
1. Control Synthesis from Linear Temporal Logic Specifications using Model-Free Reinforcement Learning
2. Survey of Model-Based Reinforcement Learning: Applications on Robotics
3. Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
4. A comprehensive survey on safe reinforcement learning;garc?a;Journal of Machine Learning Research,2015
5. Off-policy Learning for Remote Electrical Tilt Optimization
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1. Using Deep Reinforcement Learning And Formal Verification in Safety Critical Systems: Strategies and Challenges;2023 IEEE 23rd International Conference on Software Quality, Reliability, and Security Companion (QRS-C);2023-10-22
2. Network Parameter Control in Cellular Networks through Graph-Based Multi-Agent Constrained Reinforcement Learning;2023 IEEE 19th International Conference on Automation Science and Engineering (CASE);2023-08-26
3. Off-Policy Learning in Contextual Bandits for Remote Electrical Tilt Optimization;IEEE Transactions on Vehicular Technology;2023-01
4. Imperative Action Masking for Safe Exploration in Reinforcement Learning;Explainable and Transparent AI and Multi-Agent Systems;2023
5. Safe RAN control: A Symbolic Reinforcement Learning Approach;2022 IEEE 17th International Conference on Control & Automation (ICCA);2022-06-27
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