Generalized subsumption and its applications to induction and redundancy
Artificial Intelligence
A Prolog technology theorem prover: implementation by an extended Prolog computer
Journal of Automated Reasoning
Induction as nonmonotonic inference
Proceedings of the first international conference on Principles of knowledge representation and reasoning
Abduction versus closure in causal theories
Artificial Intelligence
Linear resolution for consequence finding
Artificial Intelligence
Logical settings for concept-learning
Artificial Intelligence
A new method for consequence finding and compilation in restricted languages
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
ICLP '02 Proceedings of the 18th International Conference on Logic Programming
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part II
On a Sufficient Condition for the Existence of Most Specific Hypothesis in Progol
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Causes for Events: Their Computation and Applications
Proceedings of the 8th International Conference on Automated Deduction
Which Hypotheses Can Be Found with Inverse Entailment?
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Hypothesis finding based on upward refinement of residue hypotheses
Theoretical Computer Science - Selected papers in honour of Setsuo Arikawa
A completeness theorem and a computer program for finding theorems derivable from given axioms
A completeness theorem and a computer program for finding theorems derivable from given axioms
Consequence finding and computing answers with defaults
Journal of Intelligent Information Systems
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Induction on Failure: Learning Connected Horn Theories
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
SOLAR: An automated deduction system for consequence finding
AI Communications - Practical Aspects of Automated Reasoning
Knowledge based discovery in systems biology using CF-induction
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Towards a logical reconstruction of CF-induction
JSAI'07 Proceedings of the 2007 conference on New frontiers in artificial intelligence
Mode-directed inverse entailment for full clausal theories
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Discovering rules by meta-level abduction
ILP'09 Proceedings of the 19th international conference on Inductive logic programming
Hypothesizing about causal networks with positive and negative effects by meta-level abduction
ILP'10 Proceedings of the 20th international conference on Inductive logic programming
Inductive equivalence of logic programs
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
DNF hypotheses in explanatory induction
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Does multi-clause learning help in real-world applications?
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
MC-TopLog: complete multi-clause learning guided by a top theory
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Comparison of upward and downward generalizations in CF-Induction
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Completing causal networks by meta-level abduction
Machine Learning
| Hi-index | 0.00 |
This paper presents a general procedure for inverse entailment which constructs inductive hypotheses in inductive logic programming. Based on inverse entailment, not only unit clauses but also characteristic clauses are deduced from a background theory together with the negation of positive examples. Such clauses can be computed by a resolution method for consequence finding. Unlike previous work on inverse entailment, our proposed method called CF-induction is sound and complete for finding hypotheses from full clausal theories, and can be used for inducing not only definite clauses but also non-Horn clauses and integrity constraints. We also show that CF-induction can be used to compute abductive explanations, and then compare induction and abduction from the viewpoint of inverse entailment and consequence finding.