SMT-Based Constraint Answer Set Solver EZSMT (System Description)

Constraint answer set programming is a promising research direction that integrates answer set programming with constraint processing. Recently, the formal link between this research area and satisfiability modulo theories (or SMT) was established. This link allows the cross-fertilization between traditionally different solving technologies. The paper presents the system ezsmt, one of the first SMT-based solvers for constraint answer set programming. It also presents the comparative analysis of the performance of ezsmt in relation to its peers including solvers EZCSP, CLINGCON, and MINGO. Experimental results demonstrate that SMT is a viable technology for constraint answer set programming

The EZSMT Solver: Constraint Answer Set Solving meets SMT

Constraint answer set programming is a promising research direction that integrates answer set programming with constraint processing. It is often informally related to the field of Satisfiability Modulo Theories. Yet, the exact formal link is obscured as the terminology and concepts used in these two research areas differ. In this thesis, by connecting these two areas, we begin the cross-fertilization of not only of the theoretical foundations of both areas but also of the existing solving technologies. We present the system EZSMT, one of the first solvers of this nature, which is able to take a large class of constraint answer set programs and rewrite them into Satisfiability Modulo Theories programs so that Satisfiability Modulo Theories technology can be used to process these programs

SMT-Based Answer Set Solver CMODELS(DIFF) (System Description)

Many answer set solvers utilize Satisfiability solvers for search. Satisfiability Modulo Theory solvers extend Satisfiability solvers. This paper presents the CMODELS(DIFF) system that uses Satisfiability Modulo Theory solvers to find answer sets of a logic program. Its theoretical foundation is based on Niemala\u27s characterization of answer sets of a logic program via so called level rankings. The comparative experimental analysis demonstrates that CMODELS(DIFF) is a viable answer set solver

On Relation between Constraint Answer Set Programming and Satisfiability Modulo Theories

Constraint answer set programming is a promising research direction that integrates answer set programming with constraint processing. It is often informally related to the field of satisfiability modulo theories. Yet, the exact formal link is obscured as the terminology and concepts used in these two research areas differ. In this paper, we connect these two research areas by uncovering the precise formal relation between them. We believe that this work will booster the cross-fertilization of the theoretical foundations and the existing solving methods in both areas. As a step in this direction we provide a translation from constraint answer set programs with integer linear constraints to satisfiability modulo linear integer arithmetic that paves the way to utilizing modern satisfiability modulo theories solvers for computing answer sets of constraint answer set programs.Comment: Under consideration in Theory and Practice of Logic Programming (TPLP

Evaluation Techniques and Systems for Answer Set Programming: a Survey

Answer set programming (ASP) is a prominent knowledge representation and reasoning paradigm that found both industrial and scientific applications. The success of ASP is due to the combination of two factors: a rich modeling language and the availability of efficient ASP implementations. In this paper we trace the history of ASP systems, describing the key evaluation techniques and their implementation in actual tools

Logic Programming approaches for routing fault-free and maximally-parallel Wavelength Routed Optical Networks on Chip (Application paper)

One promising trend in digital system integration consists of boosting on-chip communication performance by means of silicon photonics, thus materializing the so-called Optical Networks-on-Chip (ONoCs). Among them, wavelength routing can be used to route a signal to destination by univocally associating a routing path to the wavelength of the optical carrier. Such wavelengths should be chosen so to minimize interferences among optical channels and to avoid routing faults. As a result, physical parameter selection of such networks requires the solution of complex constrained optimization problems. In previous work, published in the proceedings of the International Conference on Computer-Aided Design, we proposed and solved the problem of computing the maximum parallelism obtainable in the communication between any two endpoints while avoiding misrouting of optical signals. The underlying technology, only quickly mentioned in that paper, is Answer Set Programming (ASP). In this work, we detail the ASP approach we used to solve such problem. Another important design issue is to select the wavelengths of optical carriers such that they are spread across the available spectrum, in order to reduce the likelihood that, due to imperfections in the manufacturing process, unintended routing faults arise. We show how to address such problem in Constraint Logic Programming on Finite Domains (CLP(FD)). This paper is under consideration for possible publication on Theory and Practice of Logic Programming.Comment: Paper presented at the 33nd International Conference on Logic Programming (ICLP 2017), Melbourne, Australia, August 28 to September 1, 2017. 16 pages, LaTeX, 5 figure

Manipulation of Articulated Objects using Dual-arm Robots via Answer Set Programming

The manipulation of articulated objects is of primary importance in Robotics, and can be considered as one of the most complex manipulation tasks. Traditionally, this problem has been tackled by developing ad-hoc approaches, which lack flexibility and portability. In this paper we present a framework based on Answer Set Programming (ASP) for the automated manipulation of articulated objects in a robot control architecture. In particular, ASP is employed for representing the configuration of the articulated object, for checking the consistency of such representation in the knowledge base, and for generating the sequence of manipulation actions. The framework is exemplified and validated on the Baxter dual-arm manipulator in a first, simple scenario. Then, we extend such scenario to improve the overall setup accuracy, and to introduce a few constraints in robot actions execution to enforce their feasibility. The extended scenario entails a high number of possible actions that can be fruitfully combined together. Therefore, we exploit macro actions from automated planning in order to provide more effective plans. We validate the overall framework in the extended scenario, thereby confirming the applicability of ASP also in more realistic Robotics settings, and showing the usefulness of macro actions for the robot-based manipulation of articulated objects. Under consideration in Theory and Practice of Logic Programming (TPLP).Comment: Under consideration in Theory and Practice of Logic Programming (TPLP

Computer Aided Verification

This open access two-volume set LNCS 13371 and 13372 constitutes the refereed proceedings of the 34rd International Conference on Computer Aided Verification, CAV 2022, which was held in Haifa, Israel, in August 2022. The 40 full papers presented together with 9 tool papers and 2 case studies were carefully reviewed and selected from 209 submissions. The papers were organized in the following topical sections: Part I: Invited papers; formal methods for probabilistic programs; formal methods for neural networks; software Verification and model checking; hyperproperties and security; formal methods for hardware, cyber-physical, and hybrid systems. Part II: Probabilistic techniques; automata and logic; deductive verification and decision procedures; machine learning; synthesis and concurrency. This is an open access book