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Team-building with answer set programming in the Gioia-Tauro seaport

THEORY AND PRACTICE OF LOGIC programming 2012年第3期12卷 361-381页

作者： Ricca, F. Grasso, G. Alviano, M. Manna, M. Lio, V. Iiritano, S. Leone, N. Univ Calabria Dipartimento Matemat I-87030 Arcavacata Di Rende Italy Univ Oxford Comp Lab Oxford OX1 3QD England Exeura Srl I-87036 Arcavacata Di Rende CS Italy

The seaport of Gioia Tauro is the largest transshipment terminal of the Mediterranean coast. A crucial management task for the companies operating in the seaport is team-building: the problem of properly allocating the available personnel for serving the incoming ships. Teams have to be carefully arranged in order to meet several constraints, such as allocation of employees with appropriate skills, fair distribution of the working load, and turnover of the heavy/dangerous roles. This makes team-building a hard and expensive task requiring several hours of manual preparation per day. In this paper we present a system based on answer set programming for the automatic generation of the teams of employees in the seaport of Gioia Tauro. The system is currently exploited in the Gioia Tauro seaport by ICO BLG, a company specialized in automobile logistics.

关键词： answer set programming declarative problem solving knowledge management workforce management artificial intelligence

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High-level synthesis of on-chip multiprocessor architectures based on answer set programming

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2018年 117卷 161-179页

作者： Bobda, Christophe Yonga, Franck Gebser, Martin Ishebabi, Harold Schaub, Torsten Univ Arkansas CSCE Dept 1 Univ Arkansas Fayetteville AR 72701 USA Univ Potsdam CS Dept August Bebel Str 89 D-14482 Potsdam Germany Amazon Vancouver 510 W Georgia St Vancouver BC V6B 0M3 Canada

We present a system-level synthesis approach for heterogeneous multi-processor on chip, based on answer set programming(ASP). Starting with a high-level description of an application, its timing constraints and the physical constraints of the target device, our goal is to produce the optimal computing infrastructure made of heterogeneous processors, peripherals, memories and communication components. Optimization aims at maximizing speed, while minimizing chip area. Also, a scheduler must be produced that fulfills the real-time requirements of the application. Even though our approach will work for application specific integrated circuits, we have chosen FPGA as target device in this work because of their reconfiguration capabilities which makes it possible to explore several design alternatives. This paper addresses the bottleneck of problem representation size by providing a direct and compact ASP encoding for automatic synthesis that is semantically equivalent to previously established ILP and ASP models. We describe a use-case in which designers specify their applications in C/C++ from which optimum systems can be derived. We demonstrate the superiority of our approach toward existing heuristics and exact methods with synthesis results on a set of realistic case studies. (C) 2018 Elsevier Inc. All rights reserved.

关键词： System design Architecture synthesis answer set programming Multi-objective optimization Technology mapping Reconfigurable architecture

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THEORY AND PRACTICE OF LOGIC programming 2013年第3期13卷 303-359页

作者： Eiter, Thomas Erdem, Esra Erdogan, Halit Fink, Michael Vienna Univ Technol Inst Informat Syst A-1040 Vienna Austria Sabanci Univ Fac Engn & Nat Sci Istanbul Turkey

For some computational problems (e. g., product configuration, planning, diagnosis, query answering, phylogeny reconstruction), computing a set of similar/diverse solutions may be desirable for better decision-making. With this motivation, we have studied several decision/optimization versions of this problem in the context of answer set programming (ASP), analyzed their computational complexity, and introduced offline/online methods to compute similar/diverse solutions of such computational problems with respect to a given distance function. All these methods rely on the idea of computing solutions to a problem by means of finding the answer sets for an ASP program that describes the problem. The offline methods compute all solutions of a problem in advance using the ASP formulation of the problem with an existing ASP solver, like clasp, and then identify similar/diverse solutions using some clustering methods (possibly in ASP as well). The online methods compute similar/diverse solutions of a problem following one of the three approaches: by reformulating the ASP representation of the problem to compute similar/diverse solutions at once using an existing ASP solver;by computing similar/diverse solutions iteratively (one after the other) using an existing ASP solver;by modifying the search algorithm of an ASP solver to compute similar/diverse solutions incrementally. All these methods are sound;the offline method and the first online method are complete whereas the others are not. We have modified clasp to implement the last online method and called it clasp-nk. In the first two online methods, the given distance function is represented in ASP;in the last one, however, it is implemented in C++. We have shown the applicability and the effectiveness of these methods using clasp or clasp-nk on two sorts of problems with different distance measures: on a real-world problem in phylogenetics (i.e., reconstruction of similar/diverse phylogenies for Indo-European languages

关键词： similar/diverse solutions answer set programming similar/diverse phylogenies similar/diverse plans

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A model building framework for answer set programming with external computations

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THEORY AND PRACTICE OF LOGIC programming 2016年第4期16卷 418-464页

作者： Eiter, Thomas Fink, Michael Ianni, Giovambattista Krennwallner, Thomas Redl, Christoph Schuller, Peter Vienna Univ Technol Inst Informat Syst Favoritenstr 9-11 A-1040 Vienna Austria Univ Calabria Dipartimento Matemat Cubo 30B I-87036 Arcavacata Di Rende CS Italy Marmara Univ Fac Engn Dept Comp Engn Goztepe Kampusu TR-34722 Istanbul Turkey

As software systems are getting increasingly connected, there is a need for equipping nonmonotonic logic programs with access to external sources that are possibly remote and may contain information in heterogeneous formats. To cater for this need, hex programs were designed as a generalization of answer set programs with an API style interface that allows to access arbitrary external sources, providing great flexibility. Efficient evaluation of such programs however is challenging, and it requires to interleave external computation and model building;to decide when to switch between these tasks is difficult, and existing approaches have limited scalability in many real-world application scenarios. We present a new approach for the evaluation of logic programs with external source access, which is based on a configurable framework for dividing the non-ground program into possibly overlapping smaller parts called evaluation units. The latter will be processed by interleaving external evaluation and model building using an evaluation graph and a model graph, respectively, and by combining intermediate results. Experiments with our prototype implementation show a significant improvement compared to previous approaches. While designed for hex-programs, the new evaluation approach may be deployed to related rule-based formalisms as well.

关键词： answer set programming model building external computation Hex programs

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Complex optimization in answer set programming

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THEORY AND PRACTICE OF LOGIC programming 2011年第4-5期11卷 821-839页

作者： Gebser, Martin Kaminski, Roland Schaub, Torsten Univ Potsdam Inst Informat Potsdam Germany Simon Fraser Univ Burnaby BC V5A 1S6 Canada Griffith Univ Nathan Qld 4111 Australia

Preference handling and optimization are indispensable means for addressing nontrivial applications in answer set programming (ASP). However, their implementation becomes difficult whenever they bring about a significant increase in computational complexity. As a consequence, existing ASP systems do not offer complex optimization capacities, supporting, for instance, inclusion-based minimization or Pareto efficiency. Rather, such complex criteria are typically addressed by resorting to dedicated modeling techniques, like saturation. Unlike the ease of common ASP modeling, however, these techniques are rather involved and hardly usable by ASP laymen. We address this problem by developing a general implementation technique by means of meta-prpogramming, thus reusing existing ASP systems to capture various forms of qualitative preferences among answer sets. In this way, complex preferences and optimization capacities become readily available for ASP applications.

关键词： answer set programming Preference Handling Complex optimization Meta-programming

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Anytime Computation of Cautious Consequences in answer set programming

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THEORY AND PRACTICE OF LOGIC programming 2014年第4-5期14卷 755-770页

作者： Alviano, Mario Dodaro, Carmine Ricca, Francesco Univ Calabria Dept Math & Comp Sci I-87036 Arcavacata Di Rende CS Italy

Query answering in answer set programming (ASP) is usually solved by computing (a subset of) the cautious consequences of a logic program. This task is computationally very hard, and there are programs for which computing cautious consequences is not viable in reasonable time. However, current ASP solvers produce the (whole) set of cautious consequences only at the end of their computation. This paper reports on strategies for computing cautious consequences, also introducing anytime algorithms able to produce sound answers during the computation.

关键词： answer set programming query answering cautious reasoning anytime algorithms

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The joy of Probabilistic answer set programming: Semantics, complexity, expressivity, inference

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INTERNATIONAL JOURNAL OF APPROXIMATE REASONING 2020年 125卷 218-239页

作者： Cozman, Fabio Gagliardi Maua, Denis Deratani Univ Sao Paulo Ctr Artificial Intelligence C4AI Sao Paulo Brazil Univ Sao Paulo Escola Politecn Sao Paulo Brazil Univ Sao Paulo Inst Matemat & Estat Sao Paulo Brazil

Probabilistic answer set programming (PASP) combines rules, facts, and independent probabilistic facts. We argue that a very useful modeling paradigm is obtained by adopting a particular semantics for PASP, where one associates a credal set with each consistent program. We examine the basic properties of PASP under this credal semantics, in particular presenting novel results on its complexity and its expressivity, and we introduce an inference algorithm to compute (upper) probabilities given a program. (C) 2020 Elsevier Inc. All rights reserved.

关键词： Logic programming answer set programming Probabilistic programming Credal sets Computational complexity Descriptive complexity

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Constraint answer set programming: Integrational and Translational (or SMT-based) Approaches

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THEORY AND PRACTICE OF LOGIC programming 2023年第1期23卷 195-225页

作者： Lierler, Yuliya Univ Nebraska Omaha NE 68182 USA

Constraint answer set programming or CASP, for short, is a hybrid approach in automated reasoning putting together the advances of distinct research areas such as answer set programming, constraint processing, and satisfiability modulo theories. CASP demonstrates promising results, including the development of a multitude of solvers: acsolver, clingcon, ezcsp, idp, inca, dingo, mingo, aspmt2smt, clingo[l,dl], and ezsmt. It opens new horizons for declarative programming applications such as solving complex train scheduling problems. Systems designed to find solutions to constraint answer set programs can be grouped according to their construction into, what we call, integrational or translational approaches. The focus of this paper is an overview of the key ingredients of the design of constraint answer set solvers drawing distinctions and parallels between integrational and translational approaches. The paper also provides a glimpse at the kind of programs its users develop by utilizing a CASP encoding of Traveling Salesman problem for illustration. In addition, we place the CASP technology on the map among its automated reasoning peers as well as discuss future possibilities for the development of CASP.

关键词： answer set programming constraints satisfiability modulo theories

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onlineSPARC: A programming Environment for answer set programming

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THEORY AND PRACTICE OF LOGIC programming 2019年第2期19卷 262-289页

作者： Marcopoulos, Elias Zhang, Yuanlin Tufts Univ Medford MA 02155 USA Texas Tech Univ Lubbock TX 79409 USA

Recent progress in logic programming (e.g. the development of the answer set programming (ASP) paradigm) has made it possible to teach it to general undergraduate and even middle/high school students. Given the limited exposure of these students to computer science, the complexity of downloading, installing, and using tools for writing logic programs could be a major barrier for logic programming to reach a much wider audience. We developed onlineSPARC, an online ASP environment with a self-contained file system and a simple interface. It allows users to type/edit logic programs and perform several tasks over programs, including asking a query to a program, getting the answer sets of a program, and producing a drawing/animation based on the answer sets of a program.

关键词： CS education logic programming answer set programming integrated development environment visualization

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Learning weak constraints in answer set programming

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THEORY AND PRACTICE OF LOGIC programming 2015年第4-5期15卷 511-525页

作者： Law, Mark Russo, Alessandra Broda, Krysia Univ London Imperial Coll Sci Technol & Med Dept Comp London SW7 2AZ England

This paper contributes to the area of inductive logic programming by presenting a new learning framework that allows the learning of weak constraints in answer set programming (ASP). The framework, called Learning from Ordered answer sets, generalises our previous work on learning ASP programs without weak constraints, by considering a new notion of examples as ordered pairs of partial answer sets that exemplify which answer sets of a learned hypothesis (together with a given background knowledge) are preferred to others. In this new learning task inductive solutions are searched within a hypothesis space of normal rules, choice rules, and hard and weak constraints. We propose a new algorithm, ILASP2, which is sound and complete with respect to our new learning framework. We investigate its applicability to learning preferences in an interview scheduling problem and also demonstrate that when restricted to the task of learning ASP programs without weak constraints, ILASP2 can be much more efficient than our previously proposed system.

关键词： Non-monotonic Inductive Logic programming Preference Learning answer set programming

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