ESSAi 2026 Course on Knowledge Compilation
The European Summer School on Artificial Intelligence
When: 6 - 10 July 2026, Vienna, Austria
Knowledge Compilation: Theory, Practice, and Applications
Speakers:
Keywords:
Knowledge Representation and Reasoning, Uncertainty in AI
Abstract:
Symbolic AI provides the foundations for transparent and explainable reasoning by grounding decisions in explicit logical or probabilistic models. Unfortunately, many reasoning tasks in that realm are computationally hard. Knowledge compilation addresses this intractability by transforming propositional models into circuits that make otherwise intractable tasks efficiently solvable. This enables fast, dependable inference and explanation over complex reasoning tasks while preserving the expressive power of the underlying models. In this short course, we introduce propositional satisfiability (SAT), modern solving techniques, and how practical solvers can be turned into engines for knowledge compilation. We examine preprocessing techniques that influence the performance and size of the compiled output. We explore different types of circuits discuss computational lower bounds, representational trade-offs, and theoretical properties that guide the choice of target languages. Finally, we demonstrate how compiled circuits enable exact model counting, uniform and weighted sampling, and direct access to structural features of the solution space.