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Using answer set programming to deal with boolean networks and attractor computation: application to gene regulatory networks of cells

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ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE 2023年第5期91卷 713-750页

作者： Khaled, Tarek Benhamou, Belaid Trinh, Van-Giang Aix Marseille Univ Univ Toulon CNRS LIS Marseille France

Deciphering gene regulatory networks' functioning is an essential step for better understanding of life, as these networks play a fundamental role in the control of cellular processes. Boolean networks have been widely used to represent gene regulatory networks. They allow to describe the dynamics of complex gene regulatory networks straightforwardly and efficiently. The attractors are essential in the analysis of the dynamics of a Boolean network. They explain that a particular cell can acquire specific phenotypes that may be transmitted over several generations. In this work, we consider a new representation of Boolean networks' dynamics based on a new semantics used in answer set programming (ASP). We use logic programs and ASP to express and deal with gene regulatory networks seen as Boolean networks, and develop a method to detect all the attractors of such networks. We first show how to represent and deal with general Boolean networks for the synchronous and asynchronous updates modes, where the computation of attractors requires a simulation of these networks' dynamics. Then, we propose an approach for the particular case of circular networks where no simulation is needed. This last specific case plays an essential role in biological systems. We show several theoretical properties;in particular, simple attractors of the gene networks are represented by the stable models of the corresponding logic programs and cyclic attractors by its extra-stable models. These extra-stable models correspond to the extra-extensions of the new semantics that are not captured by the semantics of stable models. We then evaluate the proposed approach for general Boolean networks on real biological networks and the one dedicated to the case of circular networks on Boolean networks generated randomly. The obtained results for both approaches are encouraging.

关键词： answer set programming Logic programming Systems biology Gene regulatory network Boolean network Attractor Cellular phenotype

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Industrial Applications of answer set programming

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KUNSTLICHE INTELLIGENZ 2018年第2-3期32卷 165-176页

作者： Falkner, Andreas Friedrich, Gerhard Schekotihin, Konstantin Taupe, Richard Teppan, Erich C. Alpen Adria Univ Klagenfurt Klagenfurt Austria Siemens AG Osterreich Vienna Austria

Automated problem solving in combination with declarative specifications of search-problems have shown to substantially improve the implementation and maintenance costs as well as the man-machine interaction of deployed industrial applications. The knowledge representation and reasoning (KRR) framework of answer set programming (ASP) offers a rich representation language and high performance solvers. Therefore, ASP has become very attractive for the representation and solving of search-problems both for academia and industry. This article focuses on the latest industrial applications of ASP. We do not only present successful applications of ASP but also describe the development process and the design of ASP programs in an industrial context. Finally, we discuss current approaches to tackle the most significant application challenges such as grounding and runtime improvements by heuristics.

关键词： answer set programming Applications

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Possibilistic uncertainty handling for answer set programming

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ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE 2006年第1-2期47卷 139-181页

作者： Nicolas, Pascal Garcia, Laurent Stephan, Igor Lefevre, Claire Univ Angers LERIA Angers France

In this work, we introduce a new framework able to deal with a reasoning that is at the same time non monotonic and uncertain. In order to take into account a certainty level associated to each piece of knowledge, we use possibility theory to extend the non monotonic semantics of stable models for logic programs with default negation. By means of a possibility distribution we define a clear semantics of such programs by introducing what is a possibilistic stable model. We also propose a syntactic process based on a fix-point operator to compute these particular models representing the deductions of the program and their certainty. Then, we show how this introduction of a certainty level on each rule of a program can be used in order to restore its consistency in case of the program has no model at all. Furthermore, we explain how we can compute possibilistic stable models by using available softwares for answer set programming and we describe the main lines of the system that we have developed to achieve this goal.

关键词： non monotonic reasoning uncertainty logic programming possibility theory answer set programming

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Aggregated Fuzzy answer set programming

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ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE 2011年第2期63卷 103-147页

作者： Janssen, Jeroen Schockaert, Steven Vermeir, Dirk De Cock, Martine Vrije Univ Brussel Dept Comp Sci B-1050 Brussels Belgium Univ Ghent Dept Appl Math & Comp Sci B-9000 Ghent Belgium

Fuzzy answer set programming (FASP) is an extension of answer set programming (ASP), based on fuzzy logic. It allows to encode continuous optimization problems in the same concise manner as ASP allows to model combinatorial problems. As a result of its inherent continuity, rules in FASP may be satisfied or violated to certain degrees. Rather than insisting that all rules are fully satisfied, we may only require that they are satisfied partially, to the best extent possible. However, most approaches that feature partial rule satisfaction limit themselves to attaching predefined weights to rules, which is not sufficiently flexible for most real-life applications. In this paper, we develop an alternative, based on aggregator functions that specify which (combination of) rules are most important to satisfy. We extend upon previous work by allowing aggregator expressions to define partially ordered preferences, and by the use of a fixpoint semantics.

关键词： answer set programming Fuzzy logic

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Integrating answer set programming and constraint logic programming

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ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE 2008年第1-4期53卷 251-287页

作者： Mellarkod, Veena S. Gelfond, Michael Zhang, Yuanlin Texas Tech Univ Lubbock TX 79409 USA

We introduce a knowledge representation language AC(C) extending the syntax and semantics of ASP and CR-Prolog, give some examples of its use, and present an algorithm, ACsolver, for computing answer sets of AC(C) programs. The algorithm does not require full grounding of a program and combines "classical" ASP solving methods with constraint logic programming techniques and CR-Prolog based abduction. The AC(C) based approach often allows to solve problems which are impossible to solve by more traditional ASP solving techniques. We believe that further investigation of the language and development of more efficient and reliable solvers for its programs can help to substantially expand the domain of applicability of the answer set programming paradigm.

关键词： Knowledge representation and reasoning answer set programming Constraint logic programming

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Modeling Variations of First-Order Horn Abduction in answer set programming

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FUNDAMENTA INFORMATICAE 2016年第1-2期149卷 159-207页

作者： Schuller, Peter Marmara Univ Fac Engn Dept Comp Engn Istanbul Turkey

We study abduction in First Order Horn logic theories where all atoms can be abduced and we are looking for preferred solutions with respect to three objective functions: cardinality minimality, coherence, and weighted abduction. We represent this reasoning problem in answer set programming (ASP), in order to obtain a flexible framework for experimenting with global constraints and objective functions, and to test the boundaries of what is possible with ASP. Realizing this problem in ASP is challenging as it requires value invention and equivalence between certain constants, because the Unique Names Assumption does not hold in general. To permit reasoning in cyclic theories, we formally describe fine-grained variations of limiting Skolemization. We identify term equivalence as a main instantiation bottleneck, and improve the efficiency of our approach with on-demand constraints that were used to eliminate the same bottleneck in state-of-the-art solvers. We evaluate our approach experimentally on the ACCEL benchmark for plan recognition in Natural Language Understanding. Our encodings are publicly available, modular, and our approach is more efficient than state-of-the-art solvers on the ACCEL benchmark.

关键词： First Order Horn Abduction Weighted Abduction answer set programming Natural Language Understanding

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When you must forget: Beyond strong persistence when forgetting in answer set programming

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THEORY AND PRACTICE OF LOGIC programming 2017年第5-6期17卷 837-854页

作者： Goncalves, Ricardo Knorr, Matthias Leite, Joao Woltran, Stefan Univ Nova Lisboa NOVA LINCS Lisbon Portugal TU Wien Vienna Austria

Among the myriad of desirable properties discussed in the context of forgetting in answer set programming, strong persistence naturally captures its essence. Recently, it has been shown that it is not always possible to forget a set of atoms from a program while obeying this property, and a precise criterion regarding what can be forgotten has been presented, accompanied by a class of forgetting operators that return the correct result when forgetting is possible. However, it is an open question what to do when we have to forget a set of atoms, but cannot without violating this property. In this paper, we address this issue and investigate three natural alternatives to forget when forgetting without violating strong persistence is not possible, which turn out to correspond to the different possible relaxations of the characterization of strong persistence. Additionally, we discuss their preferable usage, shed light on the relation between forgetting and notions of relativized equivalence established earlier in the context of answer set programming, and present a detailed study on their computational complexity.

关键词： forgetting answer set programming strong equivalence relativized equivalence computational complexity

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Automatic music composition using answer set programming

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THEORY AND PRACTICE OF LOGIC programming 2011年第2-3期11卷 397-427页

作者： Boenn, Georg Brain, Martin De Vos, Marina Ffitch, John Univ Glamorgan Cardiff Sch Creat & Cultural Ind Pontypridd CF37 1DL M Glam Wales Univ Bath Dept Comp Sci Bath BA2 7AY Avon England

Music composition used to be a pen and paper activity. These days music is often composed with the aid of computer software, even to the point where the computer composes parts of the score autonomously. The composition of most styles of music is governed by rules. We show that by approaching the automation, analysis and verification of composition as a knowledge representation task and formalising these rules in a suitable logical language, powerful and expressive intelligent composition tools can be easily built. This application paper describes the use of answer set programming to construct an automated system, named Anton, that can compose melodic, harmonic and rhythmic music, diagnose errors in human compositions and serve as a computer-aided composition tool. The combination of harmonic, rhythmic and melodic composition in a single framework makes Anton unique in the growing area of algorithmic composition. With near real-time composition, Anton reaches the point where it can not only be used as a component in an interactive composition tool but also has the potential for live performances and concerts or automatically generated background music in a variety of applications. With the use of a fully declarative language and an "off-the-shelf" reasoning engine, Anton provides the human composer a tool which is significantly simpler, more compact and more versatile than other existing systems.

关键词： answer set programming Applications of ASP Music composition Algorithmic composition Harmonic and melodic composition Diagnosis

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Dynamic Consistency Checking in Goal-Directed answer set programming

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THEORY AND PRACTICE OF LOGIC programming 2014年第4-5期14卷 415-427页

作者： Marple, Kyle Gupta, Gopal Univ Texas Dallas Dept Comp Sci Richardson TX 75083 USA

In answer set programming, inconsistencies arise when the constraints placed on a program become unsatisfiable. In this paper, we introduce a technique for dynamic consistency checking for our goal-directed method for computing answer sets, under which only those constraints deemed relevant to the partial answer set are tested, allowing inconsistent knowledgebases to be successfully queried. However, the algorithm guarantees that, if a program has at least one consistent answer set, any partial answer set returned will be a subset of some consistent answer set.

关键词： dynamic consistency checking answer set programming goal-directed consistent query answering

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Routing Driverless Transport Vehicles in Car Assembly with answer set programming

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THEORY AND PRACTICE OF LOGIC programming 2018年第3-4期18卷 520-534页

作者： Gebser, Martin Obermeier, Philipp Schaub, Torsten Ratsch-Heitmann, Michel Runge, Mario Univ Potsdam Potsdam Germany Mercedes Benz Ludwigsfelde GmbH Ludwigsfelde Germany

Automated storage and retrieval systems are principal components of modern production and warehouse facilities. In particular, automated guided vehicles nowadays substitute human-operated pallet trucks in transporting production materials between storage locations and assembly stations. While low-level control systems take care of navigating such driverless vehicles along programmed routes and avoid collisions even under unforeseen circumstances, in the common case of multiple vehicles sharing the same operation area, the problem remains how to set up routes such that a collection of transport tasks is accomplished most effectively. We address this prevalent problem in the context of car assembly at Mercedes-Benz Ludwigsfelde GmbH, a large-scale producer of commercial vehicles, where routes for automated guided vehicles used in the production process have traditionally been hand-coded by human engineers. Such adhoc methods may suffice as long as a running production process remains in place, while any change in the factory layout or production targets necessitates tedious manual reconfiguration, not to mention the missing portability between different production plants. Unlike this, we propose a declarative approach based on answer set programming to optimize the routes taken by automated guided vehicles for accomplishing transport tasks. The advantages include a transparent and executable problem formalization, provable optimality of routes relative to objective criteria, as well as elaboration tolerance towards particular factory layouts and production targets. Moreover, we demonstrate that our approach is efficient enough to deal with the transport tasks evolving in realistic production processes at the car factory of Mercedes-Benz Ludwigsfelde GmbH.

关键词： automated guided vehicle routing car assembly operations answer set programming

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