no code implementations • 3 Aug 2022 • 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.
no code implementations • 20 Apr 2022 • 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.
no code implementations • 9 Jul 2021 • Timo Bertram, Johannes Fürnkranz, Martin Müller
We discuss and compare two different Siamese network architectures for this task: a twin network that compares the two sets resulting after the addition, and a triplet network that models the contribution of each candidate to the existing set.
1 code implementation • 25 May 2021 • Timo Bertram, Johannes Fürnkranz, Martin Müller
Drafting, i. e., the selection of a subset of items from a larger candidate set, is a key element of many games and related problems.