Inductive Logic Programming [electronic resource] : 13th International Conference, ILP 2003, Szeged, Hungary, September 29 - October 1, 2003. Proceedings / edited by Tamás Horváth, Akihiro Yamamoto.

Invited Papers -- A Personal View of How Best to Apply ILP -- Agents that Reason and Learn -- Research Papers -- Mining Model Trees: A Multi-relational Approach -- Complexity Parameters for First-Order Classes -- A Multi-relational Decision Tree Learning Algorithm – Implementation and Experiments -- Applying Theory Revision to the Design of Distributed Databases -- Disjunctive Learning with a Soft-Clustering Method -- ILP for Mathematical Discovery -- An Exhaustive Matching Procedure for the Improvement of Learning Efficiency -- Efficient Data Structures for Inductive Logic Programming -- Graph Kernels and Gaussian Processes for Relational Reinforcement Learning -- On Condensation of a Clause -- A Comparative Evaluation of Feature Set Evolution Strategies for Multirelational Boosting -- Comparative Evaluation of Approaches to Propositionalization -- Ideal Refinement of Descriptions in -Log -- Which First-Order Logic Clauses Can Be Learned Using Genetic Algorithms? -- Improved Distances for Structured Data -- Induction of Enzyme Classes from Biological Databases -- Estimating Maximum Likelihood Parameters for Stochastic Context-Free Graph Grammars -- Induction of the Effects of Actions by Monotonic Methods -- Hybrid Abductive Inductive Learning: A Generalisation of Progol -- Query Optimization in Inductive Logic Programming by Reordering Literals -- Efficient Learning of Unlabeled Term Trees with Contractible Variables from Positive Data -- Relational IBL in Music with a New Structural Similarity Measure -- An Effective Grammar-Based Compression Algorithm for Tree Structured Data.