Inductive Logic Programming Book

	An output-polynomial time algorithm for mining frequent closed attribute trees	1
	Guiding inference through relational reinforcement learning	20
	Converting semantic meta-knowledge into inductive bias	38
	Learning teleoreactive logic programs from problem solving	51
	A framework for set-oriented computation in inductive logic programming and its application in generalizing inverse entailment	69
	Distance based generalisation	87
	Automatic induction of abduction and abstraction theories from observations	103
	Logical Bayesian networks and their relation to other probabilistic logical models	121
	Strategies to parallelize ILP systems	136
	Inducing causal laws by regular inference	154
	Online closure-based learning of relational theories	172
	Learning closed sets of labeled graphs for chemical applications	190
	ILP meets knowledge engineering : a case study	209
	Spatial clustering of structured objects	227
	Generalization behaviour of alkemic decision trees	246
	Predicate selection for structural decision trees	264
	Induction of the indirect effects of actions by monotonic methods	279
	Probabilistic first-order theory revision from examples	295
	Inductive equivalence of logic programs	312
	Deriving a stationary dynamic Bayesian network from a logic program with recursive loops	330
	A study of applying dimensionality reduction to restrict the size of a hypothesis space	348
	Polynomial time inductive inference of TTSP graph languages from positive data	366
	Classifying relational data with neural networks	384
	Efficient sampling in relational feature spaces	397
	Why computers need to learn about music	414
	Tutorial on statistical relational learning	415
	Machine learning for systems biology	416
	Five problems in five areas for five years	424