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11
Potassco: The Potsdam Answer Set Solving Collection
, 2011
"... This paper gives an overview of the open source project Potassco, the Potsdam Answer Set Solving Collection, bundling tools for Answer Set Programming developed at the University of Potsdam. ..."
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Cited by 98 (15 self)
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This paper gives an overview of the open source project Potassco, the Potsdam Answer Set Solving Collection, bundling tools for Answer Set Programming developed at the University of Potsdam.
Detecting Inconsistencies in Large Biological Networks with Answer Set Programming
, 2008
"... We introduce an approach to detecting inconsistencies in large biological networks by using Answer Set Programming. To this end, we build upon a recently proposed notion of consistency between biochemical/genetic reactions and high-throughput profiles of cell activity. We then present an approach ba ..."
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Cited by 28 (13 self)
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We introduce an approach to detecting inconsistencies in large biological networks by using Answer Set Programming. To this end, we build upon a recently proposed notion of consistency between biochemical/genetic reactions and high-throughput profiles of cell activity. We then present an approach based on Answer Set Programming to check the consistency of large-scale data sets. Moreover, we extend this methodology to provide explanations for inconsistencies in the data by determining minimal representations of conflicts. In practice, this can be used to identify unreliable data or to indicate missing reactions.
Advances in gringo series 3
- Proceedings of the 11th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR’11), 345– 351
, 2011
"... Abstract. We describe the major new features emerging from a significant redesign of the grounder gringo, building upon a grounding algorithm based on semi-naive database evaluation. Unlike previous versions, rules only need to be safe rather than domain-restricted. 1 ..."
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Cited by 20 (10 self)
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Abstract. We describe the major new features emerging from a significant redesign of the grounder gringo, building upon a grounding algorithm based on semi-naive database evaluation. Unlike previous versions, rules only need to be safe rather than domain-restricted. 1
xpanda: A (Simple) Preprocessor for Adding Multi-Valued Propositions to ASP
"... Abstract. We introduce a simple approach extending the input language of Answer Set Programming (ASP) systems by multi-valued propositions. Our approach is implemented as a (prototypical) preprocessor translating logic programs with multi-valued propositions into logic programs with Boolean proposit ..."
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Cited by 6 (1 self)
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Abstract. We introduce a simple approach extending the input language of Answer Set Programming (ASP) systems by multi-valued propositions. Our approach is implemented as a (prototypical) preprocessor translating logic programs with multi-valued propositions into logic programs with Boolean propositions only. Our translation is modular and heavily benefits from the expressive input language of ASP. The resulting approach, along with its implementation, allows for solving interesting constraint satisfaction problems in ASP, showing a good performance. 1
The BioASP Library: ASP Solutions for Systems Biology
"... Abstract—Today’s molecular biology is confronted with enormous amounts of data, generated by new high-throughput technologies, along with an increasing number of biological models available over web repositories. This poses new challenges for bioinformatics to invent methods coping with incompletene ..."
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Cited by 5 (0 self)
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Abstract—Today’s molecular biology is confronted with enormous amounts of data, generated by new high-throughput technologies, along with an increasing number of biological models available over web repositories. This poses new challenges for bioinformatics to invent methods coping with incompleteness, heterogeneity, and mutual inconsistency of data and models. To this end, we built the library BioASP, providing a framework for analyzing biological data and models with Answer Set Programming (ASP). Due to the expressive modeling language, the inherent tolerance of incomplete knowledge, and efficient solving engines, ASP has proven to be an excellent tool for solving a variety of biological questions. The BioASP library implements methods for analyzing metabolic and gene regulatory networks, consistency checking, diagnosing, and repairing biological data and models. In particular, it allows for computing predictions and generating hypotheses about required expansions of biological models. To accomplish this, expert knowledge of both the biological application and the ASP paradigm needs to be combined. In fact, the functionalities provided by the BioASP library exploit technical know-how of modeling (biological) problems in ASP and gearing ASP solvers ’ parameters to them. Often, such bestpractice technology is the result of an exhaustive series of tests. The BioASP library integrates our practical experience and offers them via easy-to-use Python functions, thus enabling ASP nonexperts to solve biological questions with ASP. I.
H.: Random vs. structure-based testing of answer-set programs: An experimental comparison
- In: Proceedings of the 11th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR 2011). Volume 6645 of Lecture Notes in Computer Science
, 2011
"... Abstract. Answer-set programming (ASP) is an established paradigm for declarative problem solving, yet comparably little work on testing of answer-set programs has been done so far. In a recent paper, foundations for structure-based testing of answer-set programs building on a number of coverage not ..."
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Cited by 3 (2 self)
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Abstract. Answer-set programming (ASP) is an established paradigm for declarative problem solving, yet comparably little work on testing of answer-set programs has been done so far. In a recent paper, foundations for structure-based testing of answer-set programs building on a number of coverage notions have been proposed. In this paper, we develop a framework for testing answer-set programs based on this work and study how good the structure-based approach to test input generation is compared to random test input generation. The results indicate that random testing is quite ineffective for some benchmarks, while structure-based techniques catch faults with a high rate more consistently also in these cases.
Technical Communications of ICLP
, 2015
"... Abstract Answer set programming is a logic programming paradigm that has increased in popularity over the past decade and found applications in a wide variety of fields. Even so, manuals written by the designers of answer set solvers usually described the semantics of the input languages of their s ..."
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Abstract Answer set programming is a logic programming paradigm that has increased in popularity over the past decade and found applications in a wide variety of fields. Even so, manuals written by the designers of answer set solvers usually described the semantics of the input languages of their systems using examples and informal comments that appeal to the users' intuition, without references to any precise semantics. We describe a precise semantics for the input language of the grounder gringo, which serves as the front end for several answer set solvers. The semantics represents gringo rules as infinitary propositional formulas. We develop methods for using this semantics to prove properties of gringo programs, such as verifying program correctness.
2.2 Basic Argumentation Frameworks....................... 4
, 2010
"... We present an experimental evaluation of popular answer-set programming (ASP) grounders and solvers that were tested with the ASP encodings for argumentation frameworks provided in the technical report “Answer-Set Programming Encodings for Argumentation Frameworks ” by Uwe Egly, Sarah Alice Gaggl an ..."
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We present an experimental evaluation of popular answer-set programming (ASP) grounders and solvers that were tested with the ASP encodings for argumentation frameworks provided in the technical report “Answer-Set Programming Encodings for Argumentation Frameworks ” by Uwe Egly, Sarah Alice Gaggl and Stefan Woltran. We made 21303 tests of randomly generated argumentation frameworks with 90-200 nodes and an edge density of 10-30 percent. The tested candidates were dlv, lparse, gringo, smodels, cmodels,
INRIA/Irisa
"... We address the problem of repairing large-scale biological networks and corresponding yet often discrepant measurements in order to predict unobserved variations. To this end, we propose a range of different operations for altering experimental data and/or a biological network in order to reestablis ..."
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We address the problem of repairing large-scale biological networks and corresponding yet often discrepant measurements in order to predict unobserved variations. To this end, we propose a range of different operations for altering experimental data and/or a biological network in order to reestablish their mutual consistency—an indispensable prerequisite for automated prediction. For accomplishing repair and prediction, we take advantage of the distinguished modeling and reasoning capacities of Answer Set Programming. We validate our framework by an empirical study on the widely investigated organism Escherichia coli.
Writing Declarative Specifications for Clauses?
"... Abstract. Modern satisfiability (SAT) solvers provide an efficient implementa-tion of classical propositional logic. Their input language, however, is based on the conjunctive normal form (CNF) of propositional formulas. To use SAT solver technology in practice, a user must create the input clauses ..."
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Abstract. Modern satisfiability (SAT) solvers provide an efficient implementa-tion of classical propositional logic. Their input language, however, is based on the conjunctive normal form (CNF) of propositional formulas. To use SAT solver technology in practice, a user must create the input clauses in one way or another. A typical approach is to write a procedural program that generates formulas on the basis of some input data relevant for the problem domain and translates them into CNF. In this paper, we propose a declarative approach where the intended clauses are specified in terms of rules in analogy to answer set programming (ASP). This allows the user to write first-order specifications for intended clauses in a schematic way by exploiting term variables. We develop a formal framework required to define the semantics of such specifications. Moreover, we provide an implementation harnessing state-of-the-art ASP grounders to accomplish the grounding step of clauses. As a result, we obtain a general-purpose clause-level grounding approach for SAT solvers. Finally, we illustrate the capabilities of our specification methodology in terms of combinatorial and application problems. 1