Reasoning Web Summer School (RW 2026), Vilnius | 27–30 August

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Linas Petkevičius

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Apr 26, 2026, 10:12:51 AM (yesterday) Apr 26

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The Reasoning Web Summer School disseminates recent advances in reasoning techniques and topics related to ontologies, rules, logic, the Semantic Web, linked data, and knowledge graph applications. It primarily targets PhD/MSc students and recent graduates, while also welcoming more senior researchers looking to catch up or deepen their knowledge. It's an excellent networking opportunity with approachable international lecturers. Confirmed Lecturers & Tutorials

Hector Geffner (RWTH Aachen University)
Learning, reasoning, and planning
Reviews a top-down approach combining symbolic and neural methods. Covers learning lifted world models, general policies/heursitics, and problem decompositions in planning. Addresses limitations of deep learning/LLMs in reasoning tasks.
Andreas Pieris (University of Cyprus & University of Edinburgh)
Rule-based Ontologies: From Semantics to Syntax
Focuses on tuple-generating dependencies (tgds) and equality-generating dependencies (egds) for data-intensive ontologies. Presents model-theoretic characterizations (semantics to syntax) of these ontology languages in symbolic AI.
Efthymia Tsamoura
A gentle introduction to the theory of neurosymbolic learning
Jonas Haldimann (University of Cape Town)
Expertise in non-monotonic reasoning, propositional conditionals, syntax splittings, belief change, and defeasible Description Logics.
Richard Booth (Cardiff University)
Non-monotonic Conditionals: A Contemporary Introduction
Covers semantic models for “if A then typically B” conditionals, inductive inference operators (rational closure, system W, disjunctive rational closure), system P, ordinal conditional functions (OCFs), syntax splitting, and knowledge-based monotony.
Nina Pardal (University of Edinburgh)
Provenance and Semiring Semantics (Abstract TBA)
Focuses on logic, KR&R, inconsistency/uncertainty, repairs, and consistent query answering.
Antonio Rago (King’s College London)
Expertise in eXplainable AI (XAI), symbolic techniques for explaining black-box models (including neural networks), with applications in recommenders, e-democracy, forecasting, etc.
Timotheus Kampik (Umeå University & SAP)
Computational Argumentation and Machine Learning
Explores synergies: using argumentation for ML (accuracy, explainability) and ML for argumentation (efficiency, convergence of semantics).
Emiliano Lorini (CNRS, IRIT Toulouse)
Reasoning About Causality
Logical languages and rule-based semantics for actual causality and counterfactuals; automation via SAT/model checking; applications in legal reasoning.
Florent Capelli (CRIL, Université d’Artois)
Knowledge compilation: Power and limits
Tractable representations of Boolean functions (for counting, sampling, optimization); algorithms, tools, applications; and lower bounds on succinctness.

Event ContextRW 2026 runs as part of Declarative AI 2026 (24–30 August), which also includes:

10th RuleML+RR 2026
13th DecisionCAMP 2026

General topic: Declarative AI – advancing rules, reasoning, decisions, and explanations for real-world impact. For the latest details, registration, and updates, visit the official site: