Invited Papers -- Actions, Causation and Logic Programming -- Challenges to Machine Learning: Relations Between Reality and Appearance -- First-Order Probabilistic Languages: Into the Unknown -- Integration of Learning and Reasoning Techniques -- Injecting Life with Computers -- Special Issue Extended Abstracts -- On the Connection Between the Phase Transition of the Covering Test and the Learning Success Rate -- Revising Probabilistic Prolog Programs -- Inductive Logic Programming for Gene Regulation Prediction -- QG/GA: A Stochastic Search for Progol -- Generalized Ordering-Search for Learning Directed Probabilistic Logical Models -- ALLPAD: Approximate Learning of Logic Programs with Annotated Disjunctions -- Margin-Based First-Order Rule Learning -- Research Papers -- Extension of the Top-Down Data-Driven Strategy to ILP -- Extracting Requirements from Scenarios with ILP -- Learning Recursive Patterns for Biomedical Information Extraction -- Towards Learning Non-recursive LPADs by Transforming Them into Bayesian Networks -- Multi-class Prediction Using Stochastic Logic Programs -- Structuring Natural Language Data by Learning Rewriting Rules -- An Efficient Algorithm for Computing Kernel Function Defined with Anti-unification -- Towards Automating Simulation-Based Design Verification Using ILP -- Minimal Distance-Based Generalisation Operators for First-Order Objects -- Efficient and Scalable Induction of Logic Programs Using a Deductive Database System -- Inductive Mercury Programming -- An ILP Refinement Operator for Biological Grammar Learning -- Combining Macro-operators with Control Knowledge -- Frequent Hypergraph Mining -- Induction of Fuzzy and Annotated Logic Programs -- Boosting Descriptive ILP for Predictive Learning in Bioinformatics -- Relational Sequence Alignments and Logos -- On the Missing Link Between Frequent Pattern Discovery and Concept Formation -- Learning Modal Theories -- A Mining Algorithm Using Property Items Extracted from Sampled Examples -- The Complexity of Translating BLPs to RMMs -- Inferring Regulatory Networks from Time Series Expression Data and Relational Data Via Inductive Logic Programming -- ILP Through Propositionalization and Stochastic k-Term DNF Learning -- ?-Subsumption Based on Object Context -- Word Sense Disambiguation Using Inductive Logic Programming -- ReMauve: A Relational Model Tree Learner -- Relational Data Mining Applied to Virtual Engineering of Product Designs.