May 13, 2024, 4:46 a.m. | Haifa Alrdahi, Riza Batista-Navarro

cs.CL updates on

arXiv:2405.06499v1 Announce Type: new
Abstract: The chess domain is well-suited for creating an artificial intelligence (AI) system that mimics real-world challenges, including decision-making. Throughout the years, minimal attention has been paid to investigating insights derived from unstructured chess data sources. In this study, we examine the complicated relationships between multiple referenced moves in a chess-teaching textbook, and propose a novel method designed to encapsulate chess knowledge derived from move-action phrases. This study investigates the feasibility of using a modified sentiment …

abstract artificial artificial intelligence arxiv attention challenges chess data data sources decision domain evaluation insights intelligence making nlp sentiment strategies study type unstructured world

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