Reinforcement learning with reward machines enables sleep control in mobile networks that accounts for history-dependent, time-averaged quality of service constraints.
Addressing function approximation error in actor-critic methods
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Event-based perception combined with progressive low-to-high speed training improves robotic table tennis return accuracy by 35.8% using the same number of training episodes.
citing papers explorer
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Reinforcement Learning with Reward Machines for Sleep Control in Mobile Networks
Reinforcement learning with reward machines enables sleep control in mobile networks that accounts for history-dependent, time-averaged quality of service constraints.
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Biologically Inspired Event-Based Perception and Sample-Efficient Learning for High-Speed Table Tennis Robots
Event-based perception combined with progressive low-to-high speed training improves robotic table tennis return accuracy by 35.8% using the same number of training episodes.