What people are saying - Write a review
We haven't found any reviews in the usual places.
BottomUp ILP Using Large Refinement Steps
On the Effect of Caching in Recursive Theory Learning
18 other sections not shown
Other editions - View all
0-subsumption abduction abstract accuracy agent aggregate conditions Aleph approach arity Artificial Intelligence atoms background knowledge caching candidate circumscriptive induction clause evaluation complete concept constraints coverage Data Mining database Datalog dataset decision tree defined Definition denote descriptive induction descriptors disjunctive domain efficiency experiments finite first-order first-order logic FOIL-D function given graph GSAT heuristic Horn clauses hypothesis ILP systems implementation inductive leap Inductive Logic Programming interpretations Jivaro L-terms language LNAI LOMDP LPADs Machine Learning macro-operators method Muggleton mutagenesis negative examples neural network node number of clauses observations parameters performance POS.CURR positive examples predicates problem procedure Progol protein pruning query Raedt random forests recursive recursive theory reduce redundant literals refinement operator reinforcement learning relational representation restarted rules score search space Section selection semantics simulated annealing solution Springer-Verlag Srinivasan step strategy subset substitution Table task Theorem theory training set tree tuples values variables