This paper develops a logical language for representing probabilistic causal laws. Our
interest in such a language is two-fold. First, it can be motivated as a fundamental study of …

Since the early days of artificial intelligence, it has been believed that logic could bring
important benefits in solving computational problems and tasks compared to standard …

In the past, there have been several attempts to explain logic programming under the well-
founded semantics as a logic of inductive definitions. A weakness in all is the absence of an …

In various domains of logic, researchers have made use of a similar intuition: that facts (or
models) can be derived from the ground up. They typically phrase this intuition by saying …

Abstract Approximation Fixpoint Theory (AFT) and Justification Theory (JT) are two
frameworks to unify logical formalisms. AFT studies semantics in terms of fixpoints of lattice …

Active integrity constraints (AICs) constitute a formalism to associate with a database not just
the constraints it should adhere to, but also how to fix the database in case one or more of …

We investigate the satisfiability problem, SAT (ID), of an extension of propositional logic with
inductive definitions. We demonstrate how to extend existing SAT solvers to become SAT …

Standard answer set programming (ASP) targets at solving search problems from the first
level of the polynomial time hierarchy (PH). Tackling search problems beyond NP using ASP …

Grounding is the task of reducing a first-order theory and finite domain to an equivalent
propositional theory. It is used as preprocessing phase in many logic-based reasoning …

A Tarskian Informal Semantics for Answer Set Programming Page 1 A Tarskian Informal Semantics
for Answer Set Programming ∗ Marc Denecker1, Yuliya Lierler2, Miroslaw Truszczynski2, and …