Abstract: Deep reinforcement learning (DRL) has been a key machine learning technique in many 5G and 6G applications. DRL agents learn optimal (or sub-optimal) policies by interacting with the ...
Learning works best when it feels reachable and uncomplicated. Children are more likely to engage when activities are easy to start, simple to follow, and flexible enough to fit different learning ...
Aim: Specific, Measurable, Achievable, Realistic, Time-bound (SMART) goals are commonly used in educational settings as a strategy to optimise learning. However, research and theory suggest that such ...
Abstract: Offline reinforcement learning (RL) enables learning policies from precollected datasets without online data collection. Although it offers the possibility to surpass the performance of the ...
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