A Fuzzy Method for Learning Simple Boolean Formulas from Examples

[1]  Bart Selman,et al.  Knowledge compilation and theory approximation , 1996, JACM.

[2]  Bruno Apolloni,et al.  Fuzzy Methods for Simplifying a Boolean Formula Inferred from Examples , 2002, FSKD.

[3]  Leslie G. Valiant,et al.  On the learnability of Boolean formulae , 1987, STOC.

[4]  Haym Hirsh,et al.  Generalizing Version Spaces , 1994, Machine Learning.

[5]  Bruno Apolloni,et al.  Algorithmic Inference in Machine Learning , 2005, IEEE Transactions on Neural Networks.

[6]  Leslie G. Valiant,et al.  A theory of the learnable , 1984, STOC '84.

[7]  Bruno Apolloni,et al.  From synapses to rules , 2002, Cognitive Systems Research.

[8]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[9]  Umesh V. Vazirani,et al.  An Introduction to Computational Learning Theory , 1994 .

[10]  Peter Clark,et al.  The CN2 Induction Algorithm , 1989, Machine Learning.

[11]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[12]  Marco Muselli,et al.  Binary Rule Generation via Hamming Clustering , 2002, IEEE Trans. Knowl. Data Eng..

[13]  Zdzislaw Pawlak,et al.  Rough Sets and Decision Algorithms , 2000, Rough Sets and Current Trends in Computing.

[14]  Manuel Laguna,et al.  Tabu Search , 1997 .

[15]  Emile H. L. Aarts,et al.  Simulated annealing and Boltzmann machines - a stochastic approach to combinatorial optimization and neural computing , 1990, Wiley-Interscience series in discrete mathematics and optimization.

[16]  Stephen Chak Tornay Ockham: studies and selections, , 1938 .

[17]  Michèle Sebag,et al.  Delaying the Choice of Bias: A Disjunctive Version Space Approach , 1996, ICML.