Parallel Answer Set Programming

Dovier, Agostino; Formisano, Andrea; Pontelli, Enrico

doi:10.1007/978-3-319-63516-3_7

Cited by 8 publications

(11 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…-There is promising work related with ethical chatbots [21] that could allow Cecilia to become more respectful to improve its ethical interaction with the student. -ASP parallelism [19,74].…”

Section: Pre-evaluation Of Ceciliamentioning

confidence: 99%

Creative Composition Problem: A Knowledge Graph Logical-Based AI Construction and Optimization Solution

Galindo

Moreno²

2021

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Contribution of this work is to Define the Creative Composition Problem (CCP) for Human Well-being Optimization by Construction of Knowledge Graph using Knowledge Representation and logic-based Artificial Intelligence reasoning-planning where the computation of the Optimal Solution is achieved by Dynamic Programming or Logic Programming. The Creative Composition Problem is embedded within Cecilia: an architecture of a digital companion artificial intelligence agent system composer of dialogue scripts for Well-being and Mental Health. Where Cecilia Framework is instantiated in Well-being and Mental Health domain for optimal well-being development of first year university students. We define the ‘The Problem of Creating a Dialogue Composition (PCDC)’ and we propose a feasible and optimal solution of it. CCP is instantiated in this applied domain to solve PCDC optimizing the Mental Health and Well-being of the student. CCP as PCDC is applied to optimize maximizing the mental health of the student but also maximizing the smoothness, coherence, enjoyment and engagement each time the dialogue session is composed. Cecilia helps students to manage stress/anxiety to attempt the prevention of depression. Students can interact through the digital companion making questions and answers. While the system “learns” from the user it allows the user to learn from herself. Once the student discovers elements that were unnoticed by her, she will find a better way to improve when discovering her points of improvement.

show abstract

Section: Pre-evaluation Of Ceciliamentioning

confidence: 99%

Creative Composition Problem: A Knowledge Graph Logical-Based AI Construction and Optimization Solution

Galindo

Moreno²

2021

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…In fact, the rules are split into two groups, the exit rules and the recursive rules, and the former are instantiated first. For more details see the original paper [6]. Then, the third phase consists of splitting a rule body atom, selected by a heuristic procedure, and partitioning its extension between several threads.…”

Section: Parallel Groundingmentioning

confidence: 99%

“…To address the latter, various techniques have been developed, divided into two groups: task sharing and scheduling. For more details, we refer the reader to the original paper [6].…”

Section: Parallel Solvingmentioning

confidence: 99%

Distributed Answer Set Coloring: Stable Models Computation via Graph Coloring

Bortoli

2019

Electron. Proc. Theor. Comput. Sci.

View full text Add to dashboard Cite

Answer Set Programming (ASP) is a famous logic language for knowledge representation, which has been really successful in the last years, as witnessed by the great interest into the development of efficient solvers for ASP. Yet, the great request of resources for certain types of problems, as the planning ones, still constitutes a big limitation for problem solving. Particularly, in the case the program is grounded before the resolving phase, an exponential blow up of the grounding can generate a huge ground file, infeasible for single machines with limited resources, thus preventing even the discovering of a single non-optimal solution. To address this problem, in this paper we present a distributed approach to ASP solving, exploiting distributed computation benefits in order to overcome the just explained limitations. The here presented tool, which is called Distributed Answer Set Coloring (DASC), is a pure solver based on the well-known Graph Coloring algorithm. DASC is part of a bigger project aiming to bring logic programming into a distributed system, started in 2017 by Federico Igne with mASPreduce and continued in 2018 by Pietro Totis with a distributed grounder. In this paper we present a low level implementation of the Graph Coloring algorithm, via the Boost and MPI libraries for C++. Finally, we provide a few results of the very first working version of our tool, at the moment without any strong optimization or heuristic.I want to thank Fabio Tardivo, Agostino Dovier and Enrico Pontelli for their support during the development of the tool.

show abstract

“…Steps have been made in the last decade toward the parallelization of the basic components of Logic Programming systems. Implementations of solvers exploiting multicore architectures, distributed systems, or portfolio approaches, have been proposed [4]. In this direction, a recent new stream of research concerns the design and development of parallel ASP systems that can take advantage of the massive degree of parallelism offered by modern Graphical Processing Units (GPUs).…”

Section: Introductionmentioning

confidence: 99%

GPU-based parallelism for ASP-solving

Dovier¹,

Formisano²,

Vella³

2019

Preprint

Self Cite

View full text Add to dashboard Cite

Answer Set Programming (ASP) has become, the paradigm of choice in the field of logic programming and non-monotonic reasoning. Thanks to the availability of efficient solvers, ASP has been successfully employed in a large number of application domains. The term GPU-computing indicates a recent programming paradigm aimed at enabling the use of modern parallel Graphical Processing Units (GPUs) for general purpose computing. In this paper we describe an approach to ASP-solving that exploits GPU parallelism. The design of a GPUbased solver poses various challenges due to the peculiarities of GPUs' software and hardware architectures and to the intrinsic nature of the satisfiability problem.

show abstract

Parallel Answer Set Programming

Cited by 8 publications

References 58 publications

Creative Composition Problem: A Knowledge Graph Logical-Based AI Construction and Optimization Solution

Creative Composition Problem: A Knowledge Graph Logical-Based AI Construction and Optimization Solution

Distributed Answer Set Coloring: Stable Models Computation via Graph Coloring

GPU-based parallelism for ASP-solving

Contact Info

Product

Resources

About