Abstract—Learning from small data is a challenge that presents itself in applications of human-robot interaction (HRI).
Learning from small data is a challenge that presents itself in applications of human-robot interaction (HRI) in the context of pediatric rehabilitation.
Learning from small data is a challenge that presents itself in applications of human-robot interaction (HRI) in the context of pediatric rehabilitation.
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Abstract. Efficient planning plays a crucial role in model-based reinforcement learning. Tradi- tionally, the main planning operation is a.
Mar 23, 2018 · I have a large set of simulation logs for a market simulation of which I want to learn from. The market includes:.
Missing: option small
We consider the problem of reinforcement learning in factored-state MDPs in the setting in which learning is conducted in one long trial with no resets ...
Nov 27, 2017 · While MDPs with options can be mapped to SMDPs, their analysis cannot be immediately translated into the PAC-MDP sample complexity of learning.
Jun 23, 2023 · Active learning is a machine learning method that involves iteratively selecting the most informative samples from the available data pool for ...
Mar 27, 2021 · For starters, what is Reinforcement Learning? When we learn in the real world, we are subconsciously aware of our surroundings and how they ...
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