Cooling schedules for optimal annealing
Mathematics of Operations Research
Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
An analysis of first-order logics of probability
Artificial Intelligence
Learning structured concepts using genetic algorithms
ML92 Proceedings of the ninth international workshop on Machine learning
C4.5: programs for machine learning
C4.5: programs for machine learning
The nature of statistical learning theory
The nature of statistical learning theory
Mathematical Methods for Neural Network Analysis and Design
Mathematical Methods for Neural Network Analysis and Design
Learning Logical Definitions from Relations
Machine Learning
Learning Probabilistic Relational Models
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
DOGMA: A GA-Based Relational Learner
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Search-intensive concept induction
Evolutionary Computation
Unbiased assessment of learning algorithms
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Coping with exceptions in multiclass ILP problems using possibilistic logic
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Learnability of description logic programs
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
A genetic algorithms approach to ILP
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Lattice-search runtime distributions may be heavy-tailed
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Placement by Simulated Annealing on a Multiprocessor
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Formal behavior modeling and effective automatic refinement
Information Sciences: an International Journal
A Randomized Exhaustive Propositionalization Approach for Molecule Classification
INFORMS Journal on Computing
Optimizing least-significant-bit substitution using cat swarm optimization strategy
Information Sciences: an International Journal
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In Inductive Logic Programming (ILP), algorithms that are purely of the bottom-up or top-down type encounter several problems in practice. Since a majority of them are greedy ones, these algorithms stop when finding clauses in local optima, according to the ''quality'' measure used for evaluating the results. Moreover, when learning clauses one by one, the induced clauses become less and less interesting as the algorithm is progressing to cover few remaining examples. In this paper, we propose a simulated annealing framework to overcome these problems. Using a refinement operator, we define neighborhood relations on clauses and on hypotheses (i.e. sets of clauses). With these relations and appropriate quality measures, we show how to induce clauses (in a coverage approach), or to induce hypotheses directly by using simulated annealing algorithms. We discuss the necessary conditions on the refinement operators and the evaluation measures to increase the effectiveness of the algorithm. Implementations (included a parallelized version of the algorithm) are described and experimentation results in terms of convergence of the method and in terms of accuracy are presented.