scholarly journals An Answer Set Programming Approach to Argumentative Reasoning in the ASPIC+ Framework

2020 ◽  
Author(s):  
Tuomo Lehtonen ◽  
Johannes P. Wallner ◽  
Matti Järvisalo
Keyword(s):  
Answer Set Programming ◽  
Research Direction ◽  
Programming Approach ◽  
Computational Techniques ◽  
Major Research ◽  
Structured Argumentation ◽  
Algorithmic Techniques ◽  
Argumentative Reasoning ◽  
Significant Size ◽  
Answer Set

A major research direction in AI argumentation is the study and development of practical computational techniques for reasoning in different argumentation formalisms. Compared to abstract argumentation, developing algorithmic techniques for different structured argumentation formalisms, such as assumption-based argumentation and the general ASPIC+ framework, is more challenging. At present, there is a lack of efficient approaches to reasoning in ASPIC+. We develop a direct declarative approach based on answer set programming (ASP) to reasoning in an instantiation of the ASPIC+ framework. We establish formal foundations for direct declarative encodings for reasoning in ASPIC+ without preferences for several central argumentation semantics, and detail ASP encodings of semantics for which reasoning about acceptance is NP-hard in ASPIC+. Empirically, the ASP approach scales up to frameworks of significant size, thereby answering the current lack of practical computational approaches to reasoning in ASPIC+ and providing a promising base for capturing further generalizations within ASPIC+.

scholarly journals Harnessing Incremental Answer Set Solving for Reasoning in Assumption-Based Argumentation

2021 ◽  
pp. 1-18
Author(s):  
TUOMO LEHTONEN ◽  
JOHANNES P. WALLNER ◽  
MATTI JӒRVISALO
Keyword(s):  
Logic Programming ◽  
Answer Set Programming ◽  
Polynomial Hierarchy ◽  
Np Hard ◽  
Abstraction Refinement ◽  
Recent Advances ◽  
Structured Argumentation ◽  
Reasoning Tasks ◽  
Answer Set

Abstract Assumption-based argumentation (ABA) is a central structured argumentation formalism. As shown recently, answer set programming (ASP) enables efficiently solving NP-hard reasoning tasks of ABA in practice, in particular in the commonly studied logic programming fragment of ABA. In this work, we harness recent advances in incremental ASP solving for developing effective algorithms for reasoning tasks in the logic programming fragment of ABA that are presumably hard for the second level of the polynomial hierarchy, including skeptical reasoning under preferred semantics as well as preferential reasoning. In particular, we develop non-trivial counterexample-guided abstraction refinement procedures based on incremental ASP solving for these tasks. We also show empirically that the procedures are significantly more effective than previously proposed algorithms for the tasks.

scholarly journals Semantic-based construction of arguments: An answer set programming approach

2015 ◽  
Vol 64 ◽  
pp. 54-74 ◽  
Author(s):  
Esteban Guerrero ◽  
Juan Carlos Nieves ◽  
Helena Lindgren
Keyword(s):  
Answer Set Programming ◽  
Programming Approach ◽  
Answer Set

scholarly journals Human Robot Collaborative Assembly Planning: An Answer Set Programming Approach

2020 ◽  
Vol 20 (6) ◽  
pp. 1006-1020
Author(s):  
Momina Rizwan ◽  
Volkan Patoglu ◽  
Esra Erdem
Keyword(s):  
Cognitive Skills ◽  
Answer Set Programming ◽  
Assembly Planning ◽  
Programming Approach ◽  
Planning Under Uncertainty ◽  
Commonsense Reasoning ◽  
Collaborative Assembly ◽  
High Level ◽  
Assembly Tasks ◽  
Answer Set

AbstractFor planning an assembly of a product from a given set of parts, robots necessitate certain cognitive skills: high-level planning is needed to decide the order of actuation actions, while geometric reasoning is needed to check the feasibility of these actions. For collaborative assembly tasks with humans, robots require further cognitive capabilities, such as commonsense reasoning, sensing, and communication skills, not only to cope with the uncertainty caused by incomplete knowledge about the humans’ behaviors but also to ensure safer collaborations. We propose a novel method for collaborative assembly planning under uncertainty, that utilizes hybrid conditional planning extended with commonsense reasoning and a rich set of communication actions for collaborative tasks. Our method is based on answer set programming. We show the applicability of our approach in a real-world assembly domain, where a bi-manual Baxter robot collaborates with a human teammate to assemble furniture.

scholarly journals Logic programming approaches for routing fault-free and maximally parallel wavelength-routed optical networks-on-chip (Application paper)

2017 ◽  
Vol 17 (5-6) ◽  
pp. 800-818 ◽  
Author(s):  
MARCO GAVANELLI ◽  
MADDALENA NONATO ◽  
ANDREA PEANO ◽  
DAVIDE BERTOZZI
Keyword(s):  
Logic Programming ◽  
Optical Networks ◽  
Computer Aided Design ◽  
Optimization Problems ◽  
Answer Set Programming ◽  
Programming Approach ◽  
Optical Carrier ◽  
Networks On Chip ◽  
On Chip ◽  
Answer Set

AbstractOne 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. 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. In this work, we detail the Answer Set Programming 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.

scholarly journals On relation between constraint answer set programming and satisfiability modulo theories

2017 ◽  
Vol 17 (4) ◽  
pp. 559-590
Author(s):  
YULIYA LIERLER ◽  
BENJAMIN SUSMAN
Keyword(s):  
Answer Set Programming ◽  
Research Direction ◽  
Linear Constraints ◽  
Satisfiability Modulo Theories ◽  
Research Areas ◽  
Formal Relation ◽  
Answer Sets ◽  
Theoretical Foundations ◽  
Cross Fertilization ◽  
Answer Set

AbstractConstraint 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 boost 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.

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