A Model to Study Phase Transition and Plateaus in Relational Learning

DOI10.1007/978-3-540-85928-4_6zbMath1156.68515OpenAlexW1782545736MaRDI QIDQ3543267

Erick Alphonse, Aomar Osmani

Publication date: 2 December 2008

Published in: Inductive Logic Programming (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-85928-4_6

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)

Performances of pure random walk algorithms on constraint satisfaction problems with growing domains

Cites Work

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• On the connection between the phase transition of the covering test and the learning success rate in ILP
• Random constraint satisfaction: easy generation of hard (satisfiable) instances
• Subsumption and implication
• The hardest constraint problems: A double phase transition
• Phase transitions in relational learning
• Locating the phase transition in binary constraint satisfaction problems
• 10.1162/153244304773936018
• Extension of the Top-Down Data-Driven Strategy to ILP
• Inductive Logic Programming
• Constructing an asymptotic phase transition in random binary constraint satisfaction problems

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