Minimal unsatisfiability describes the reduced kernel of unsatisfiable formulas. The
investigation of this property is very helpful in understanding the reasons for unsatisfiability …

We study the complexity of invariant inference and its connections to exact concept learning.
We define a condition on invariants and their geometry, called the fence condition, which …

This paper proposes to use prime implicants and prime implicates normal forms to represent
belief sets. This representation is used, on the one hand, to define syntactical versions of …

Concluding this mini-series of 2 articles on the foundations of generalised clause-sets, we
study the combinatorial properties of non-boolean conjunctive normal forms (clause-sets) …

We consider the problem of generalising boolean formulas in conjunctive normal form by
allowing non-boolean variables, with the goal of maintaining combinatorial properties …

The objective of machine learning is to acquire knowledge from available information in an
automated manner. As an example, one can think of obtaining rules for medical diagnosis …

We aim at providing a foundation of a theory of" good" SAT representations F of boolean
functions f. We argue that the hierarchy UC_k of unit-refutation complete clause-sets of level …

Knowledge Compilation (KC) studies compilation of boolean functions f into some formalism
F, which allows to answer all queries of a certain kind in polynomial time. Due to its …

Minimal unsatisfiability describes the reduced kernel of unsatisfiable formulas. The
investigation of this property is very helpful in understanding the reasons for unsatisfiability …

Selman and Kautz [22] proposed an approach to compute a Horn CNF approximation of
CNF formulas. We extend this approach and propose a new algorithm for the Horn least …