An Information-Based Neural Approach to Constraint Satisfaction

DOI10.1162/08997660152469369zbMath0986.68106DBLPjournals/neco/JonssonS01arXivcond-mat/0105319OpenAlexW2162953554WikidataQ52056964 ScholiaQ52056964MaRDI QIDQ2746341

Bo Söderberg, Henrik Jönsson

Publication date: 10 October 2001

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/cond-mat/0105319

zbMATH Keywords

artificial neural networkdiscrete constraint satisfaction problems

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (1)

An information-based neural approach to generic constraint satisfaction.

Cites Work

• Determining computational complexity from characteristic ‘phase transitions’

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