16 citations · 19 across the 5 of their papers we have counts for
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cs.AI2022
Supervised and Reinforcement Learning from Observations in Reconnaissance Blind Chess
Timo Bertram, Johannes Fürnkranz, Martin Müller
In this work, we adapt a training approach inspired by the original AlphaGo system to play the imperfect information game of Reconnaissance Blind Chess. Using only the observations…
cs.LG2022★ 1 cited
Quantity vs Quality: Investigating the Trade-Off between Sample Size and Label Reliability
Timo Bertram, Johannes Fürnkranz, Martin Müller
In this paper, we study learning in probabilistic domains where the learner may receive incorrect labels but can improve the reliability of labels by repeatedly sampling them. In s…