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 295
... constructed for the tabulated cases above are as fol- lows . propositional animals : class ( A , mammal ) has_milk ( A , true ) . ← Table 2 : Times taken for constructing and reducing various Efficient Induction of Logic Programs 295.
... constructed for the tabulated cases above are as fol- lows . propositional animals : class ( A , mammal ) has_milk ( A , true ) . ← Table 2 : Times taken for constructing and reducing various Efficient Induction of Logic Programs 295.
Page 446
... constructed that mentions an infinite value . A model induced by GOLEM from all 10 examples was : legalstate ( la ... constructed this model using 10 examples and 5408 background atoms representing the necessary atoms from QSIM theory ...
... constructed that mentions an infinite value . A model induced by GOLEM from all 10 examples was : legalstate ( la ... constructed this model using 10 examples and 5408 background atoms representing the necessary atoms from QSIM theory ...
Page 542
... Constructing Initial Theories from Observations Suppose another agent in the world has constructed an arch ( yet again ! ) . CAP would try to construct a theory that describes the preconditions and post - conditions of each action in ...
... Constructing Initial Theories from Observations Suppose another agent in the world has constructed an arch ( yet again ! ) . CAP would try to construct a theory that describes the preconditions and post - conditions of each action in ...
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