Communications of the ACM
Learning regular sets from queries and counterexamples
Information and Computation
Logic programming
Identification of unions of languages drawn from an identifiable class
COLT '89 Proceedings of the second annual workshop on Computational learning theory
Prediction-preserving reducibility
Journal of Computer and System Sciences - 3rd Annual Conference on Structure in Complexity Theory, June 14–17, 1988
Learning elementary formal systems
Theoretical Computer Science
Short note: procedural semantics and negative information of elementary formal system
Journal of Logic Programming
Lower Bound Methods and Separation Results for On-Line Learning Models
Machine Learning - Computational learning theory
Rich classes inferable from positive data
Information and Computation
Towards a mathematical theory of machine discovery from facts
Theoretical Computer Science - Special issue on algorithmic learning theory
When won't membership queries help?
Selected papers of the 23rd annual ACM symposium on Theory of computing
Machine Learning - Special issue on COLT '94
Elementary formal systems, intrinsic complexity, and procrastination
Information and Computation
Learning unions of tree patterns using queries
Theoretical Computer Science - Special issue on algorithmic learning theory
Learning Function-Free Horn Expressions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
Inductive inference of unbounded unions of pattern languages from positive data
Theoretical Computer Science - Special issue on algorithmic learning theory
Polynomial-time learning of elementary formal systems
New Generation Computing
Algorithmic Program DeBugging
Machine Learning
Machine Learning
Constructive Learning of Context-Free Languages with a Subpansive Tree
ICGI '00 Proceedings of the 5th International Colloquium on Grammatical Inference: Algorithms and Applications
Iterated Transductions and Efficient Learning from Positive Data: A Unifying View
ICGI '00 Proceedings of the 5th International Colloquium on Grammatical Inference: Algorithms and Applications
Polynomial Time Inference of Extended Regular Pattern Languages
Proceedings of RIMS Symposium on Software Science and Engineering
STACS '94 Proceedings of the 11th Annual Symposium on Theoretical Aspects of Computer Science
Learning Pattern Languages Using Queries
EuroCOLT '97 Proceedings of the Third European Conference on Computational Learning Theory
Inductive Inference of an Approximate Concept from Positive Data
AII '94 Proceedings of the 4th International Workshop on Analogical and Inductive Inference: Algorithmic Learning Theory
On Approximately Identifying Concept Classes in the Limit
ALT '95 Proceedings of the 6th International Conference on Algorithmic Learning Theory
Learning Acyclic First-Order Horn Sentences from Entailment
ALT '97 Proceedings of the 8th International Conference on Algorithmic Learning Theory
Learning languages from positive data and a finite number of queries
Information and Computation
Learning languages from positive data and a finite number of queries
Information and Computation
Learning of elementary formal systems with two clauses using queries
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
Learning languages from positive data and a finite number of queries
FSTTCS'04 Proceedings of the 24th international conference on Foundations of Software Technology and Theoretical Computer Science
Inductive logic programming: yet another application of logic
INAP'05 Proceedings of the 16th international conference on Applications of Declarative Programming and Knowledge Management
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The elementary formal system (EFS) is a kind of logic programs which directly manipulates strings, and the learnability of the subclass called hereditary EFSs (HEFSs) has been investigated in the frameworks of the PAC-learning, query-learning, and inductive inference models. The hierarchy of HEFS is expressed by HEFS(m,k,t,r), where m, k, t and r denote the number of clauses, the occurrences of variables in the head, the number of atoms in the body, and the arity of predicate symbols. The present paper deals with the learnability of HEFS in the query learning model using equivalence queries and additional queries such as membership, predicate membership, entailment membership, and dependency queries. We show that the class HEFS(*, k, t, r) is polynomial-time learnable with the equivalence and predicate membership queries and the class HEFS(*,k,*,r) with termination property is polynomial-time learnable with the equivalence, entailment membership, and dependency queries for the unbounded parameter *. A lowerbound on the number of queries is presented. We also show that the class HEFS(*,k,t,r) is hard to learn with the equivalence and membership queries under the cryptographic assumptions. Furthermore, the learnability of the class of unions of regular pattern languages, which is a subclass of HEFSs, is investigated. The bounded unions of regular pattern languages are polynomial-time predictable with membership query. However, all unbounded unions of regular pattern languages are not polynomial-time predictable with membership queries if neither are the DNF formulas.