5 citations · 12 across the 3 of their papers we have counts for
3 papers
cs.AI2015★ 5 cited
Evolving Non-linear Stacking Ensembles for Prediction of Go Player Attributes
Josef Moudřík, Roman Neruda
The paper presents an application of non-linear stacking ensembles for prediction of Go player attributes. An evolutionary algorithm is used to form a diverse ensemble of base lear…
cs.AI2015★ 5 cited
Evaluating Go Game Records for Prediction of Player Attributes
Josef Moudřík, Petr Baudiš, Roman Neruda
We propose a way of extracting and aggregating per-move evaluations from sets of Go game records. The evaluations capture different aspects of the games such as played patterns or…
cs.AI2012★ 2 cited
On Move Pattern Trends in a Large Go Games Corpus
Petr Baudiš, Josef Moudřík
We process a large corpus of game records of the board game of Go and propose a way of extracting summary information on played moves. We then apply several basic data-mining metho…