Structure and Learning (Dagstuhl Seminar 21362)

Autor:	Dong, Tiansi, Rettinger, Achim, Tang, Jie, Tversky, Barbara, van Harmelen, Frank
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	Knowledge graph Machine learning Computing methodologies ��� Artificial intelligence Computing methodologies ��� Machine learning Computing methodologies ��� Symbolic and algebraic manipulation Neural-symbol unification
DOI:	10.4230/dagrep.11.8.11
Popis:	This report documents the program and the outcomes of Dagstuhl Seminar 21362 "Structure and Learning", held from September 5 to 10, 2021. Structure and learning are among the most prominent topics in Artificial Intelligence (AI) today. Integrating symbolic and numeric inference was set as one of the next open AI problems at the Townhall meeting "A 20 Year Roadmap for AI" at AAAI 2019. In this Dagstuhl seminar, we discussed related problems from an interdiscplinary perspective, in particular, Cognitive Science, Cognitive Psychology, Physics, Computational Humor, Linguistic, Machine Learning, and AI. This report overviews presentations and working groups during the seminar, and lists two open problems. DagRep, Volume 11, Issue 8, pages 11-34
Databáze:	OpenAIRE
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