Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
We present a new and very simple translation of the bounded model checking problem which is linear both in the size of the formula and the length of the bound. The resulting CNF-fo...
Timo Latvala, Armin Biere, Keijo Heljanko, Tommi A...
This paper presents an algorithm that achieves hyper-arc consistency for the soft alldifferent constraint. To this end, we prove and exploit the equivalence with a minimum-cost flo...
Scalability is recognized as a key challenge in the automated analysis of Feature Models (FMs). Current solutions in this context mainly propose using different logic paradigms as...
In this note we study the existence of a solution to the survey-propagation equations for the random K-satisfiability problem for a given instance. We conjecture that when the num...