Answer Set Programming is a well-established paradigm of declarative programming in close
relationship with other declarative formalisms such as SAT Modulo Theories, Constraint …

We consider planning with uncertainty in the initial state as a case study of incremental
quantified Boolean formula (QBF) solving. We report on experiments with a workflow to …

The goal of this paper is a systematic parameterized complexity analysis of different variants
of propositional STRIPS planning. We identify several natural problem parameters and …

Backdoors are a powerful tool to obtain efficient algorithms for hard problems. Recently, two
new notions of backdoors to planning were introduced. However, for one of the new notions (…

Disjunctive answer set programming (ASP) is an important framework for declarative modeling
and problem solving, where the computational complexity of basic decision problems like …

One of the fundamental goals in computer science is to understand the computational
complexity of important problems. Many of these important problems have been proven to be …

Planning is everywhere. In our everyday life we have developed very fast methods to produce
good plans for simple tasks. However, when the complexity of the problem grows, we …

Backdoors measure the distance to tractable fragments and have become an important tool
to find fixed-parameter tractable (fpt) algorithms for hard problems in AI and beyond. Despite …

Backdoors measure the distance to tractable fragments and have become an important tool
to find fixed-parameter tractable (fpt) algorithms. Despite their success, backdoors have not …

An effective way to model message exchange in complex settings is to use UML sequence
diagrams in combination with state machine diagrams. A natural question that arises in this …