Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Minimal and complete word unification
Journal of the ACM (JACM)
Inductive inference of monotonic formal systems from positive data
New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
Learning elementary formal systems
Theoretical Computer Science
Short note: procedural semantics and negative information of elementary formal system
Journal of Logic Programming
Complexity of unification problems with associative-commutative operators
Journal of Automated Reasoning
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
Efficient string matching: an aid to bibliographic search
Communications of the ACM
Constructive Learning of Translations Based on Dictionaries
ALT '96 Proceedings of the 7th International Workshop on Algorithmic Learning Theory
Learnability of Translations from Positive Examples
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
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An EFS is a kind of logic programs expressing various formal languages. We propose an efficient derivation for EFS's called an S-derivation, where every possible unifiers are evaluated at one step of the derivation. In the S-derivation, each unifier is partially applied to each goal clause by assigning variables whose values are uniquely determined from the set of all possible unifiers. This contributes to reduce the number of backtracking, and thus the S-derivation works efficiently. In this paper, the S-derivation is shown to be complete for the class of regular EFS's.We implement an EFS interpreter based on the S-derivation in Prolog programming language, and compare the parsing time with that of DCG provided by the Prolog interpreter. As the results of experiments, we verify the efficiency of the S-derivation for accepting context-free languages.