
selp: A SingleShot Epistemic Logic Program Solver
Epistemic Logic Programs (ELPs) are an extension of Answer Set Programmi...
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Train Scheduling with Hybrid Answer Set Programming
We present a solution to realworld train scheduling problems, involving...
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ASP(AC): Answer Set Programming with Algebraic Constraints
Weighted Logic is a powerful tool for the specification of calculations ...
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A Uniform Treatment of Aggregates and Constraints in Hybrid ASP
Characterizing hybrid ASP solving in a generic way is difficult since on...
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Clingo goes Linear Constraints over Reals and Integers
The recent series 5 of the ASP system clingo provides generic means to e...
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SemiQuantitative Abstraction and Analysis of Chemical Reaction Networks
Analysis of large continuoustime stochastic systems is a computationall...
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A Hybrid Data Cleaning Framework using Markov Logic Networks
With the increase of dirty data, data cleaning turns into a crux of data...
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Hybrid Metabolic Network Completion
Metabolic networks play a crucial role in biology since they capture all chemical reactions in an organism. While there are networks of high quality for many model organisms, networks for less studied organisms are often of poor quality and suffer from incompleteness. To this end, we introduced in previous work an ASPbased approach to metabolic network completion. Although this qualitative approach allows for restoring moderately degraded networks, it fails to restore highly degraded ones. This is because it ignores quantitative constraints capturing reaction rates. To address this problem, we propose a hybrid approach to metabolic network completion that integrates our qualitative ASP approach with quantitative means for capturing reaction rates. We begin by formally reconciling existing stoichiometric and topological approaches to network completion in a unified formalism. With it, we develop a hybrid ASP encoding and rely upon the theory reasoning capacities of the ASP system clingo for solving the resulting logic program with linear constraints over reals. We empirically evaluate our approach by means of the metabolic network of Escherichia coli. Our analysis shows that our novel approach yields greatly superior results than obtainable from purely qualitative or quantitative approaches. Under consideration in Theory and Practice of Logic Programming (TPLP).
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