A Semantic Perspective on Omission Abstraction in ASP

2020 ◽  
Author(s):  
Zeynep G. Saribatur ◽  
Thomas Eiter
Keyword(s):  
Problem Solving ◽  
Program Analysis ◽  
Abstract Level ◽  
Answer Sets

The recently introduced notion of ASP abstraction is on reducing the vocabulary of a program while ensuring over-approximation of its answer sets, with a focus on having a syntactic operator that constructs an abstract program. It has been shown that such a notion has the potential for program analysis at the abstract level by getting rid of irrelevant details to problem solving while preserving the structure, that aids in the explanation of the solutions. We take here a further look on ASP abstraction, focusing on abstraction by omission with the aim to obtain a better understanding of the notion. We distinguish the key conditions for omission abstraction which sheds light on the differences to the well-studied notion of forgetting. We demonstrate how omission abstraction fits into the overall spectrum, by also investigating its behavior in the semantics of a program in the framework of HT logic.

scholarly journals Grounding and Solving in Answer Set Programming

AI Magazine ◽  
2016 ◽  
Vol 37 (3) ◽  
pp. 25-32 ◽  
Author(s):  
Benjamin Kaufmann ◽  
Nicola Leone ◽  
Simona Perri ◽  
Torsten Schaub
Keyword(s):  
Problem Solving ◽  
Propositional Logic ◽  
Logic Program ◽  
Answer Set Programming ◽  
Key Issues ◽  
Answer Sets ◽  
Answer Set

Answer set programming is a declarative problem solving paradigm that rests upon a workflow involving modeling, grounding, and solving. While the former is described by Gebser and Schaub (2016), we focus here on key issues in grounding, or how to systematically replace object variables by ground terms in a effective way, and solving, or how to compute the answer sets of a propositional logic program obtained by grounding.

scholarly journals ANALISIS RESPON MAHASISWAPGSD DALAM MENYELESAIKAN SOAL IPABERDASARKAN STRUCTURE OF OBSERVED LEARNING OUTCOME TAXONOMY DITINJAU DARI MOTIVASI BELAJAR

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Siti Fatimah
Keyword(s):  
Qualitative Research ◽  
Problem Solving ◽  
Research Method ◽  
Learning Outcome ◽  
Data Sources ◽  
Motivation To Learn ◽  
Solo Taxonomy ◽  
High Category ◽  
Abstract Level

SOLO Taxonomy is one of the frameworks used in analyzing the quality of responses in problem solving. This research aim to analyze the student’s responses level in doing problem solving item based on SOLO Taxonomy overviewed from motivation to learn. The research method used in this study was a qualitative research with the data sources of this study were 75 students period 2016/2017. The results of the study showed that student’s responses in doing problem solving wave concept at prestructural level is 62,17%, Unistructural Level is 27,63%, Multistructural level is 58,22%, Relasional level is 48,50%, and Extended Abstract level is 37,82%; Motivation to learn’s student high category are better at responding to answer item based SOLO Taxonomy than motivation to learn’s students low category.Keywords: Student’s reponses; SOLO Taxonomy; Motivation to Learn

scholarly journals ANALISIS RESPON MAHASISWAPGSD DALAM MENYELESAIKAN SOAL IPABERDASARKAN STRUCTURE OF OBSERVED LEARNING OUTCOME TAXONOMY DITINJAU DARI MOTIVASI BELAJAR

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Siti Fatimah
Keyword(s):  
Qualitative Research ◽  
Problem Solving ◽  
Research Method ◽  
Learning Outcome ◽  
Data Sources ◽  
Motivation To Learn ◽  
Solo Taxonomy ◽  
High Category ◽  
Abstract Level

SOLO Taxonomy is one of the frameworks used in analyzing the quality of responses in problem solving. This research aim to analyze the student’s responses level in doing problem solving item based on SOLO Taxonomy overviewed from motivation to learn. The research method used in this study was a qualitative research with the data sources of this study were 75 students period 2016/2017. The results of the study showed that student’s responses in doing problem solving wave concept at prestructural level is 62,17%, Unistructural Level is 27,63%, Multistructural level is 58,22%, Relasional level is 48,50%, and Extended Abstract level is 37,82%; Motivation to learn’s student high category are better at responding to answer item based SOLO Taxonomy than motivation to learn’s students low category.Keywords: Student’s reponses; SOLO Taxonomy; Motivation to Learn

scholarly journals ALGEBRA PROBLEM SOLVING ABILITY BASED ON SOLO TAXONOMY ASSESSED FROM COGNITIVE STYLE

2021 ◽  
Vol 12 (2) ◽  
pp. 148
Author(s):  
Arie Purwa Kusuma ◽  
S B Waluya ◽  
Rochmad Rochmad ◽  
S Mariani
Keyword(s):  
Problem Solving ◽  
Cognitive Style ◽  
Cognitive Styles ◽  
Sampling Technique ◽  
Research Subjects ◽  
Solo Taxonomy ◽  
Abstract Level ◽  
The Relationship ◽  
Matching Familiar Figures Test ◽  
Student Problem

Algebra is a branch of mathematics that uses mathematical statements to describe the relationship between various things. This study aims to describe the algebra problem solving abilities of students in the Linear Program course. There are differences in student problem solving, which are caused by students' cognitive styles. Reflective and impulsive cognitive styles based on the SOLO taxonomy. This research method is descriptive qualitative. The research was conducted at STKIP Kusuma Negara Jakarta. The research subjects consisted of 4 students, 2 students having a reflective cognitive style and 2 students having an impulsive style. Purposive sampling technique was used in taking the subjects.Data collection techniques used cognitive style test questions Matching Familiar Figures Test (MFFT), algebra problem solving test questions and interview guidelines. Data collection techniques used two techniques, namely written tests and interviews. Technical analysis of data by reducing data, presenting data, and drawing conclusions. From the data processing, the results of the research were 2 students whose have flexible cognitive style also have good algebra problem solving abilities and based on SOLO taxonomy reached the Extended abstract level. Meanwhile, students who have an impulsive cognitive style in solving algebra problems based more on the SOLO taxonomy have Multistructural and Unistructural levels. So each cognitive style of students gives the different results in solving problems.

scholarly journals Better Paracoherent Answer Sets with Less Resources

2019 ◽  
Vol 19 (5-6) ◽  
pp. 757-772 ◽  
Author(s):  
GIOVANNI AMENDOLA ◽  
CARMINE DODARO ◽  
FRANCESCO RICCA
Keyword(s):  
Problem Solving ◽  
Equilibrium Model ◽  
State Of The Art ◽  
Answer Set Programming ◽  
Evaluation Technique ◽  
Answer Set Semantics ◽  
Computational Resources ◽  
Answer Sets ◽  
Modeling Feature ◽  
Answer Set

AbstractAnswer Set Programming (ASP) is a well-established formalism for logic programming. Problem solving in ASP requires to write an ASP program whose answers sets correspond to solutions. Albeit the non-existence of answer sets for some ASP programs can be considered as a modeling feature, it turns out to be a weakness in many other cases, and especially for query answering. Paracoherent answer set semantics extend the classical semantics of ASP to draw meaningful conclusions also from incoherent programs, with the result of increasing the range of applications of ASP. State of the art implementations of paracoherent ASP adopt the semi-equilibrium semantics, but cannot be lifted straightforwardly to compute efficiently the (better) split semi-equilibrium semantics that discards undesirable semi-equilibrium models. In this paper an efficient evaluation technique for computing a split semi-equilibrium model is presented. An experiment on hard benchmarks shows that better paracoherent answer sets can be computed consuming less computational resources than existing methods.

scholarly journals Omission-Based Abstraction for Answer Set Programs

2020 ◽  
pp. 1-51 ◽  
Author(s):  
ZEYNEP G. SARIBATUR ◽  
THOMAS EITER
Keyword(s):  
Problem Solving ◽  
Answer Set Programming ◽  
Search Space ◽  
Complex Problem ◽  
Experimental Results ◽  
Partial Answer ◽  
Abstraction Refinement ◽  
The Cost ◽  
Answer Sets ◽  
Answer Set

Abstract Abstraction is a well-known approach to simplify a complex problem by over-approximating it with a deliberate loss of information. It was not considered so far in Answer Set Programming (ASP), a convenient tool for problem solving. We introduce a method to automatically abstract ASP programs that preserves their structure by reducing the vocabulary while ensuring an over-approximation (i.e., each original answer set maps to some abstract answer set). This allows for generating partial answer set candidates that can help with approximation of reasoning. Computing the abstract answer sets is intuitively easier due to a smaller search space, at the cost of encountering spurious answer sets. Faithful (non-spurious) abstractions may be used to represent projected answer sets and to guide solvers in answer set construction. For dealing with spurious answer sets, we employ an ASP debugging approach to help with abstraction refinement, which determines atoms as badly omitted and adds them back in the abstraction. As a show case, we apply abstraction to explain unsatisfiability of ASP programs in terms of blocker sets, which are the sets of atoms such that abstraction to them preserves unsatisfiability. Their usefulness is demonstrated by experimental results.

scholarly journals TCHR: a framework for tabled CLP

2008 ◽  
Vol 8 (04) ◽  
pp. 491-526 ◽  
Author(s):  
TOM SCHRIJVERS ◽  
BART DEMOEN ◽  
DAVID S. WARREN
Keyword(s):  
Logic Programming ◽  
Program Analysis ◽  
Ad Hoc ◽  
Constraint Logic Programming ◽  
Control Performance ◽  
Level System ◽  
High Level ◽  
New Applications ◽  
Answer Sets ◽  
Application Specific

AbstractTabled Constraint Logic Programming is a powerful execution mechanism for dealing with Constraint Logic Programming without worrying about fixpoint computation. Various applications, e.g. in the fields of program analysis and model checking, have been proposed. Unfortunately, a high-level system for developing new applications is lacking, and programmers are forced to resort to complicated ad hoc solutions.This papers presents TCHR, a high-level framework for tabled Constraint Logic Programming. It integrates in a light-weight manner Constraint Handling Rules (CHR), a high-level language for constraint solvers, with tabled Logic Programming. The framework is easily instantiated with new application-specific constraint domains. Various high-level operations can be instantiated to control performance. In particular, we propose a novel, generalized technique for compacting answer sets.

scholarly journals Profil Pemecahan Masalah Aljabar Berpandu Pada Taksonomi SOLO Ditinjau Dari Gaya Kognitif Konseptual Tempo Siswa SMA Negeri 1 Makale Tana Toraja [A Profile of Guided Algebra Problem Solving Using the SOLO Taxonomy and the Cognitive Conceptual Tempo Style of Students at the SMA Negeri 1 School In Makale, Tana Toraja]

2017 ◽  
Vol 13 (2) ◽  
pp. 47
Author(s):  
Oce Datu Appulembang
Keyword(s):  
Problem Solving ◽  
Linear Equation ◽  
Cognitive Style ◽  
Learning Outcomes ◽  
Cognitive Test ◽  
Solo Taxonomy ◽  
Familiar Figure ◽  
Abstract Level ◽  
Figure Test ◽  
Main Instrument

<p>The objective of this research was to discover the process used in solving a superitem test which consisted of 4 stages according to the SOLO (Structure of Learning Outcomes) Taxonomy, namely unistuctural, multistructural, relational, and extended abstract, and reviewed using the cognitive impulsive and reflective style. The research was qualitative research. The main instrument of the research was the researcher himself guided by a superitem test, an impulsive-reflective cognitive test namely MFFT (Matching Familiar Figure Test), and a valid interview guideline. The subject of this research was the students of class X<sub>1</sub> at SMA Negeri 1 Makale Tana Toraja consisting of four students in which 2 subjects were with cognitive impulsive style and 2 subjects with cognitive reflective style. The data was collected by giving a superitem test which was verified with an interview. The results of the research show that: (a) the first subject’s impulsive and reflective style showed the tendency of problem solving at an abstract level which was expanded in the question of one variable linear equation and in the question of two variable linear equation, (b) the second subject’s impulsive cognitive style in two variable linear equation problem solving showed the tendency of unistuctural and relational thinking only, (c) the second subject’s cognitive reflective style showed the tendency of problem solving in relational level, (d) the subject’s impulsive and reflective cognitive style showed the tendency of the same problem solving in the level unistructural, multistructural, relational, and abstract in the question of one variable linear equation, and different in the abstract level in the question of two variable linear equation.</p><p>BAHASA INDONESIA ABSTRAK: Tujuan penelitian ini adalah untuk mengetahui profil pemecahan masalah dengan melihat dan mengungkap proses berpikir siswa dalam menyelesaikan tes superitem yang terdiri atas 4 tingkatan menurut Taksonomi SOLO (<em>Structure of Observed Learning Outcomes</em>), yaitu: unistruktural, multistruktural, relasional, dan abstrak yang diperluas ditinjau dari gaya kognitif impulsif dan reflektif. Penelitian ini merupakan penelitian deskriptif dengan pendekatan kualitatif. Instrumen utama dalam penelitian ini adalah peneliti sendiri yang dipandu oleh tes superitem, tes gaya kognitif impulsif-reflektif, yaitu: MFFT (<em>Matching Familiar Figure Test</em>), dan pedoman wawancara yang valid. Subjek penelitian ini adalah siswa kelas X<sub>1</sub> SMA Negeri 1 Makale Tana Toraja yang terdiri dari 4 subjek yang mana 2 subjek gaya kognitif impulsif dan 2 subjek gaya kognitif reflektif. Pengumpulan data dilakukan dengan pemberian tes superitem dan verifikasi dengan wawancara. Hasil penelitian ini adalah (a) Subjek pertama gaya kognitif impulsif (GKI) maupun reflektif (GKR) menunjukkan kecenderungan pemecahan masalah pada tingkat abstrak yang diperluas pada soal persamaan linear satu variabel dan soal persamaan linear dua variabel, (b) Subjek kedua gaya kognitif impulsif pada pemecahan masalah persamaan linear dua variabel menunjukkan kecenderungan berpikir unistruktural dan relasional saja, (c) Subjek kedua gaya kognitif reflektif (GKR) menunjukkan kecenderungan pemecahan masalah pada tingkat relasional, (d) Subjek gaya kognitif impulsif maupun reflektif menunjukkan kecenderungan pemecahan masalah yang sama pada tingkat unistruktural, multistruktural, relasional dan abstrak pada soal persamaan linear satu variabel, dan berbeda pada tingkat abstrak pada soal persamaan linear dua variabel.</p>

The effect of teaching method on endodontic problem solving

1982 ◽  
Vol 46 (9) ◽  
pp. 548-552 ◽  
Author(s):  
RW Mendel ◽  
JP Scheetz
Keyword(s):  
Problem Solving ◽  
Teaching Method
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