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Researcher profile

Jo Devriendt

Jo Devriendt contributes to research discovery and scholarly infrastructure.

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Artificial Intelligence

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Published work

4 published item(s)

preprint2026arXiv

Transforming Constraint Programs to Input for Local Search

Applying local search algorithms to combinatorial optimization problems is not an easy feat. Typically, human intervention is required to compile the constraints to input data for some metaheuristic algorithm. In this paper, we establish a link between symmetry properties of constraint optimization problems and local search neighborhoods, and we use this link to automatically generate neighborhoods from a constraint specification in the context of the IDP system. We evaluate the obtained neighborhoods for six classical optimization problems. The resulting observations support the viability of this technique.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

BreakID: Static Symmetry Breaking for ASP (System Description)

Symmetry breaking has been proven to be an efficient preprocessing technique for satisfiability solving (SAT). In this paper, we port the state-of-the-art SAT symmetry breaker BreakID to answer set programming (ASP). The result is a lightweight tool that can be plugged in between the grounding and the solving phases that are common when modelling in ASP. We compare our tool with sbass, the current state-of-the-art symmetry breaker for ASP.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Implementing a Relevance Tracker Module

PC(ID) extends propositional logic with inductive definitions: rule sets under the well-founded semantics. Recently, a notion of relevance was introduced for this language. This notion determines the set of undecided literals that can still influence the satisfiability of a PC(ID) formula in a given partial assignment. The idea is that the PC(ID) solver can make decisions only on relevant literals without losing soundness and thus safely ignore irrelevant literals. One important insight that the relevance of a literal is completely determined by the current solver state. During search, the solver state changes have an effect on the relevance of literals. In this paper, we discuss an incremental, lightweight implementation of a relevance tracker module that can be added to and interact with an out-of-the-box SAT(ID) solver.

0 citations0 reviewsNo code linkedOpen access