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 149
... correct with 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 with 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 ( ...
Page 150
... correct wrt M } be the correct part of R * ( T ) and S = { E : E is a clause which is correct wrt M and there exists D € R * ( T ) – Q and DNE and for every E ' , DE ' E only if E ' incorrect wrt M } be a specialization of the incorrect ...
... correct wrt M } be the correct part of R * ( T ) and S = { E : E is a clause which is correct wrt M and there exists D € R * ( T ) – Q and DNE and for every E ' , DE ' E only if E ' incorrect wrt M } be a specialization of the incorrect ...
Page 151
... correct - specialization of T. Assume that there exists Q ' which is a correct- specialization of T and QUSH Q ' . Thus , applying Lemma 4 , it is not the case that for every clause F , F is in Q ' only if there exists a clause G such ...
... correct - specialization of T. Assume that there exists Q ' which is a correct- specialization of T and QUSH Q ' . Thus , applying Lemma 4 , it is not the case that for every clause F , F is in Q ' only if there exists a clause G such ...
Contents
Inductive Logic Programming | 4 |
A Framework for Inductive Logic Programming | 9 |
3 | 21 |
Copyright | |
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0-subsumes abstraction operators applied approach arguments arity Artificial Intelligence background knowledge Buntine C₁ C₂ CIGOL CLINT Closed World Assumption complete Computer concept description constrained atoms constraint predicates constraint theory constructed contains defined definite clauses 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 inductive learning Inductive Logic Programming inference input instance instantiation integrity constraints intended interpretation inverse resolution learnable learning algorithms Lemma LINUS literals Machine Learning method Morgan Kaufmann Muggleton multi-valued logic Negation as Failure negative examples non-monotonic logic occur oracle PAC-learning polynomial positive examples problem Prolog proof tree relation representation restricted RLGG rules saturation Section set of clauses Shapiro skolemized sort theory sorted atoms sparky specific subset substitution T₁ target Theorem true truncation tuples unit clauses variables