Aug. 29, 2022, 1:11 a.m. | Attila Egri-Nagy, Antti Törmänen

cs.LG updates on arXiv.org arxiv.org

AI engines utilizing deep learning neural networks provide excellent tools
for analyzing traditional board games. Here we are interested in gaining new
insights into the ancient game of Go. For that purpose, we need to define new
numerical measures based on the raw output of the engines. In this paper, we
develop a numerical tool for automated move-by-move performance evaluation in a
context-sensitive manner and for recognizing game features. We measure the
urgency of a move by the cost of …

ai arxiv cost deep learning game go learning understanding

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