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. |
From inside the book
Results 1-3 of 88
Page 119
... operator A is a mapping from clauses to sets of clauses , such that : where A ' A ( p ) = { p } U A ' { qqp and size ( p ) > size ( q ) } . Any such operator A induces an operator ( also denoted A ) which takes sets of clauses to sets ...
... operator A is a mapping from clauses to sets of clauses , such that : where A ' A ( p ) = { p } U A ' { qqp and size ( p ) > size ( q ) } . Any such operator A induces an operator ( also denoted A ) which takes sets of clauses to sets ...
Page 269
... operator in CIGOL constructs C2 given C1 and C. Within the propositional Duce system the identification operator constructs C1 given C2 and C. The identification operator has not yet been implemented in CIGOL . These two operators ...
... operator in CIGOL constructs C2 given C1 and C. Within the propositional Duce system the identification operator constructs C1 given C2 and C. The identification operator has not yet been implemented in CIGOL . These two operators ...
Page 415
... operator . This conclusion suggests that it would be more interesting to use inverse resolution as an extra intelligent operator together with uninformed ones , rather than designing a concept learning algorithm with inverse resolution ...
... operator . This conclusion suggests that it would be more interesting to use inverse resolution as an extra intelligent operator together with uninformed ones , rather than designing a concept learning algorithm with inverse resolution ...
Contents
Inductive Logic Programming | 4 |
A Framework for Inductive Logic Programming | 9 |
3 | 21 |
Copyright | |
44 other sections not shown
Other editions - View all
Common terms and phrases
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