A statistical approach to learning constraints

DOI10.1016/j.ijar.2024.109184MaRDI QIDQ6577673

Steven Prestwich, Nic Wilson

Publication date: 24 July 2024

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

zbMATH Keywords

sequential analysissequential hypothesis testingconstraint learningconstraint acquisition

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37)

Cites Work

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• Constraint acquisition
• Empirical decision model learning
• Clausal discovery
• Truncated sequential probability ratio test
• First-order \(jk\)-clausal theories are PAC-learnable
• Progress towards the Holy Grail
• Time-bounded query generator for constraint acquisition
• Automatic synthesis of constraints from examples using mixed integer linear programming
• Sequential experimentation in clinical trials. Design and analysis
• Classifier-based constraint acquisition
• A theory of the learnable
• Turing’s anticipation of empirical bayes in connection with the cryptanalysis of the naval enigma^*
• Embedding Decision Trees and Random Forests in Constraint Programming
• Sequential Tests of Statistical Hypotheses
• Principles and Practice of Constraint Programming – CP 2004

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Synergies between machine learning and reasoning -- an introduction by the Kay R. Amel group

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