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The representation of a dynamic problem in ASP usually boils down to using copies of variables and constraints, one for each time stamp, no matter whether it is directly encoded or via an action or temporal language. The multiplication of…

Artificial Intelligence · Computer Science 2025-06-11 Javier Romero , Torsten Schaub , Klaus Strauch

We propose a new formal language for the expressive representation of probabilistic knowledge based on Answer Set Programming (ASP). It allows for the annotation of first-order formulas as well as ASP rules and facts with probabilities and…

Artificial Intelligence · Computer Science 2014-05-06 Matthias Nickles , Alessandra Mileo

In spite of the recent improvements in the performance of the solvers based on the DPLL procedure, it is still possible for the search algorithm to focus on the wrong areas of the search space, preventing the solver from returning a…

Artificial Intelligence · Computer Science 2015-03-18 Marcello Balduccini

The design of embedded systems, that are ubiquitously used in mobile devices and cars, is becoming continuously more complex such that efficient system-level design methods are becoming crucial. My research aims at developing systems that…

Artificial Intelligence · Computer Science 2019-05-15 Philipp Wanko

We propose Differentiable Satisfiability and Differentiable Answer Set Programming (Differentiable SAT/ASP) for multi-model optimization. Models (answer sets or satisfying truth assignments) are sampled using a novel SAT/ASP solving…

Artificial Intelligence · Computer Science 2019-01-01 Matthias Nickles

Broad application of answer set programming (ASP) for declarative problem solving requires the development of tools supporting the coding process. Program debugging is one of the crucial activities within this process. Recently suggested…

Artificial Intelligence · Computer Science 2014-10-29 Kostyantyn Shchekotykhin

Modern solvers for Boolean Satisfiability (SAT) and Answer Set Programming (ASP) are based on sophisticated Boolean constraint solving techniques. In both areas, conflict-driven learning and related techniques constitute key features whose…

Artificial Intelligence · Computer Science 2015-03-17 Christian Drescher , Martin Gebser , Benjamin Kaufmann , Torsten Schaub

Combining a set of existing constraint solvers into an integrated system of cooperating solvers is a useful and economic principle to solve hybrid constraint problems. In this paper we show that this approach can also be used to integrate…

Programming Languages · Computer Science 2007-05-23 Petra Hofstedt , Peter Pepper

Non-stationary domains, where unforeseen changes happen, present a challenge for agents to find an optimal policy for a sequential decision making problem. This work investigates a solution to this problem that combines Markov Decision…

Artificial Intelligence · Computer Science 2017-05-04 Leonardo A. Ferreira , Reinaldo A. C. Bianchi , Paulo E. Santos , Ramon Lopez de Mantaras

A wide range of problems can be modelled as constraint satisfaction problems (CSPs), that is, a set of constraints that must be satisfied simultaneously. Constraints can either be represented extensionally, by explicitly listing allowed…

Artificial Intelligence · Computer Science 2013-07-09 Evgenij Thorstensen

A wide range of problems can be modelled as constraint satisfaction problems (CSPs), that is, a set of constraints that must be satisfied simultaneously. Constraints can either be represented extensionally, by explicitly listing allowed…

Artificial Intelligence · Computer Science 2015-02-10 Evgenij Thorstensen

The dominating set reconfiguration problem is defined as determining, for a given dominating set problem and two among its feasible solutions, whether one is reachable from the other via a sequence of feasible solutions subject to a certain…

Artificial Intelligence · Computer Science 2025-01-22 Masato Kato , Torsten Schaub , Takehide Soh , Naoyuki Tamura , Mutsunori Banbara

The rise of powerful AI technology for a range of applications that are sensitive to legal, social, and ethical norms demands decision-making support in presence of norms and regulations. Normative reasoning is the realm of deontic logics,…

Logic in Computer Science · Computer Science 2023-08-31 Christian Hatschka , Agata Ciabattoni , Thomas Eiter

Over the past decades, Answer Set Programming (ASP) has emerged as an important paradigm for declarative problem solving. Technological progress in this area has been stimulated by the use of common standards, such as the ASP-Core-2…

Artificial Intelligence · Computer Science 2021-08-10 Kylian Van Dessel , Jo Devriendt , Joost Vennekens

Answer Set Programming (ASP) provides a powerful declarative paradigm for knowledge representation and reasoning. Recently, counting answer sets has emerged as an important computational problem with applications in probabilistic reasoning,…

Logic in Computer Science · Computer Science 2025-07-17 Mohimenul Kabir , Supratik Chakraborty , Kuldeep S Meel

Epistemic logic programs (ELPs) are a popular generalization of standard Answer Set Programming (ASP) providing means for reasoning over answer sets within the language. This richer formalism comes at the price of higher computational…

Computational Complexity · Computer Science 2020-01-14 Markus Hecher , Michael Morak , Stefan Woltran

We take up an idea from the folklore of Answer Set Programming, namely that choices, integrity constraints along with a restricted rule format is sufficient for Answer Set Programming. We elaborate upon the foundations of this idea in the…

Artificial Intelligence · Computer Science 2021-11-25 Jorge Fandinno , Seemran Mishra , Javier Romero , Torsten Schaub

Answer Set Programming (ASP) is a declarative logic programming formalism, which is employed nowadays in both academic and industrial real-world applications. Although some tools for supporting the development of ASP programs have been…

Programming Languages · Computer Science 2011-08-30 Onofrio Febbraro , Nicola Leone , Kristian Reale , Francesco Ricca

This technical report describes the usage, syntax, semantics and core algorithms of the probabilistic inductive logic programming framework PrASP. PrASP is a research software which integrates non-monotonic reasoning based on Answer Set…

Artificial Intelligence · Computer Science 2017-01-02 Matthias Nickles

Answer set programming (ASP) is a paradigm for declarative problem solving where problems are first formalized as rule sets, i.e., answer-set programs, in a uniform way and then solved by computing answer sets for programs. The…

Artificial Intelligence · Computer Science 2011-08-31 Mai Nguyen , Tomi Janhunen , Ilkka Niemelä