The Constraint Reasoning and Optimization group, led by Associate Professor Matti Järvisalo, focuses on the development and analysis of state-of-the-art decision, search, and optimization procedures, and their applications in computationally hard problem domains with real-world relevance. Especially, the group contributes to the development state-of-the-art Boolean satisfiability (SAT) solvers, their extensions to Boolean optimization, and applications of SAT-based and other types of discrete search and optimization procedures in exactly solving intrinsically hard (NP-complete and beyond) computational tasks. Recent domain-specific directions include exact approaches to solving machine learning related optimization problems and computational aspects of argumentation theory.
Constraint Reasoning and Optimization
Paper accepted to Theory and Practice of Logic Programming
In the article, the authors harness recent advances in incremental answer set solving for developing effective algorithms for reasoning tasks in...
Paper accepted to FOCS 2021
The work presents the first 2-approximation algorithm for treewidth that is faster than known exact algorithms.
Paper accepted to Artificial Intelligence Journal
The article provides and detailed overview the 2020 SAT Competition and an extended empirical analysis of the results of the competition.
Four papers accepted to CP 2021
Four research papers by the Constraint Reasoning and Optimization Group have been accepted for publication in the proceedings of CP 2021, a...
First Place in Model Counting Competition 2021
The SharpSAT-TD exact propositional model counter, implemented by Tuukka Korhonen of the Constraint Reasoning and Optimization group, ranks...