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 59
... variables that already occur in a for other variables in a reduces height - bound ( a ) because it reduces the number , m , of variables in a , and it changes the values of no other parameters in the definition of height- bound ( a ) ...
... variables that already occur in a for other variables in a reduces height - bound ( a ) because it reduces the number , m , of variables in a , and it changes the values of no other parameters in the definition of height- bound ( a ) ...
Page 324
... variables ( referred to as old variables ) . The number of literals added in each case is given below : 1. b1 = 2x ( old ) = Old × ( Old − 1 ) : there are ( Old ) distinct choices of pairs of old variables ; 2. b2 , i - - = 2 × [ ( Old ...
... variables ( referred to as old variables ) . The number of literals added in each case is given below : 1. b1 = 2x ( old ) = Old × ( Old − 1 ) : there are ( Old ) distinct choices of pairs of old variables ; 2. b2 , i - - = 2 × [ ( Old ...
Page 347
... variables are re- placed with predicates can be true or false . These considerations lead directly to the definition ... variables as used in the definition of ≥ we use a substitution Σ applied to predicate variables to rename or ...
... variables are re- placed with predicates can be true or false . These considerations lead directly to the definition ... variables as used in the definition of ≥ we use a substitution Σ applied to predicate variables to rename or ...
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