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Certified MaxSAT Preprocessing
Building on the progress in Boolean satisfiability (SAT) solving over the last decades, maximum satisfiability (MaxSAT) has become a viable approach...
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Structure-Guided Cube-and-Conquer for MaxSAT
We present a black-box inprocessor for the partially weighted maximum satisfiability problem, which extends any given MaxSAT solver with inprocessing...
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Certified Core-Guided MaxSAT Solving
In the last couple of decades, developments in SAT-based optimization have led to highly efficient maximum satisfiability (MaxSAT) solvers, but in...
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MaxSAT-based temporal logic inference from noisy data
We address the problem of inferring descriptions of system behavior using temporal logic from a finite set of positive and negative examples. In this...
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Interpretable decision trees through MaxSAT
We present an approach to improve the accuracy-interpretability trade-off of Machine Learning (ML) Decision Trees (DTs). In particular, we apply...
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The MaxSAT Problem in the Real-Valued MV-Algebra
This work addresses the maximum satisfiability (MaxSAT) problem for a multiset of arbitrary formulas of the language of propositional Łukasiewicz...
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Inference in MaxSAT and MinSAT
Logical calculi applied to solve SAT are unsound for MaxSAT and MinSAT because they preserve satisfiability but not the minimum and the maximum...
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An Incremental MaxSAT-Based Model to Learn Interpretable and Balanced Classification Rules
The increasing advancements in the field of machine learning have led to the development of numerous applications that effectively address a wide...
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A MaxSAT Solver Based on Differential Evolution (Preliminary Report)
In this paper we present DeMaxSAT, a memetic algorithm for solving the non-partial MaxSAT problem. It combines the evolutionary algorithm of...
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Scaling up Nonmonotonic c-Inference via Partial MaxSAT Problems
Ranking functions, also called ordinal conditional functions (OCF), provide a semantics for conditionals by assigning a degree of implausibility to...
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On Preprocessing for Weighted MaxSAT
Modern competitive solvers employ various preprocessing techniques to efficiently tackle complex problems. This work introduces two preprocessing...
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QMaxSATpb: A Certified MaxSAT Solver
While certification has been successful in the context of satisfiablity solving, with most state-of-the-art solvers now able to provide proofs of...
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Core Boosting in SAT-Based Multi-objective Optimization
Maximum satisfiability (MaxSAT) constitutes today a successful approach to solving various real-world optimization problems through propositional...
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Learning Linear Temporal Properties from Noisy Data: A MaxSAT-Based Approach
We address the problem of inferring descriptions of system behavior using Linear Temporal Logic (LTL) from a finite set of positive and negative...
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An abstract view on optimizations in propositional frameworks
Search/optimization problems are plentiful in scientific and engineering domains. Artificial intelligence has long contributed to the development of...
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Maximum Satisfiability of Mission-Time Linear Temporal Logic
Mission-time Linear Temporal Logic (MLTL) is a variant of Linear Temporal Logic (LTL) with finite interval bounds on temporal operators, and is a...
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MaxSAT-Based Postprocessing for Treedepth
Treedepth is an increasingly popular graph invariant. Many NP-hard combinatorial problems can be solved efficiently on graphs of bounded treedepth....
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DiagDO: an efficient model based diagnosis approach with multiple observations
Model-based diagnosis (MBD) with multiple observations shows its significance in identifying fault location. The existing approaches for MBD with...
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On Some Variants of the Merging Variables Based (1+1)-Evolutionary Algorithm with Application to MaxSAT Problem
In this paper we describe a new evolutionary strategy. It is based on the common (1+1) random mutation scheme which was augmented with metaheuristic...
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Clause Redundancy and Preprocessing in Maximum Satisfiability
The study of clause redundancy in Boolean satisfiability (SAT) has proven significant in various terms, from fundamental insights into preprocessing...