Inductive Logic ProgrammingStephen Muggleton Inductive logic programming is a new research area emerging at present. Whilst inheriting various positive characteristics of the parent subjects of logic programming an machine learning, it is hoped that the new area will overcome many of the limitations of its forbears. This book describes the theory, implementations and applications of Inductive Logic Programming. |
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Page 49
... respect to a fixed background theory Σ . An oracle for equivalence queries answers yes to any given query if the predicted sentence is equivalent to the target with respect to Σ ; it answers no otherwise . The oracle gives a counter ...
... respect to a fixed background theory Σ . An oracle for equivalence queries answers yes to any given query if the predicted sentence is equivalent to the target with respect to Σ ; it answers no otherwise . The oracle gives a counter ...
Page 149
... respect to M , or simply F is correct , whenever M is a model of F. F is said to be incorrect otherwise . An implementation of this definition would allow for correction of a formula with respect to known facts . Lemma 1 ( Correct ...
... respect to M , or simply F is correct , whenever M is a model of F. F is said to be incorrect otherwise . An implementation of this definition would allow for correction of a formula with respect to known facts . Lemma 1 ( Correct ...
Page 290
... respect to Bm + 1 if and only if for every substitution 0 such that A0 € E and { B1 , ... , Bm } 0 C M ( K ) there is a unique atom Bm + 108 in M ( K ) , i.e. , for any such 0 there is a unique valid ground substitution 8 whose domain ...
... respect to Bm + 1 if and only if for every substitution 0 such that A0 € E and { B1 , ... , Bm } 0 C M ( K ) there is a unique atom Bm + 108 in M ( K ) , i.e. , for any such 0 there is a unique valid ground substitution 8 whose domain ...
Contents
Inductive Logic Programming | 4 |
A Framework for Inductive Logic Programming | 9 |
A Study of Constrained | 29 |
Copyright | |
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absorption abstraction operators applied approach arguments arity Artificial Intelligence background knowledge body Buntine C₁ C₂ CIGOL clause logic CLINT Closed World Assumption complete Computer concept descriptions constrained atoms constraint predicates constraint theory constructed contains defined derivation described domain theory e₁ efficient facts Figure finite first-order first-order logic flattening FOCL FOIL formula framework function symbols given GOLEM ground clause head heuristic Horn clauses hypothesis implied incremental inductive learning Inductive Logic Programming inference input instances instantiation integrity constraints intended interpretation inverse resolution knowledge base learnable Lemma LINUS literals Machine Learning method Morgan Kaufmann Muggleton multi-valued logic negative examples non-monotonic logic oracle PAC-learnable polynomial positive examples problem Prolog proof tree queries recursive representation resolution step restricted result RLGG rules saturation Section set of clauses Shapiro skolemized sort theory sorted atoms sparky specific subset substitution target Theorem tion true truncation tuples unit clauses variables