Towards Lazy Grounding with Lazy Normalization in Answer-Set Programming (Extended Abstract)

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Standard

Towards Lazy Grounding with Lazy Normalization in Answer-Set Programming (Extended Abstract). / Bomanson, Jori; Janhunen, Tomi; Weinzierl, Antonius.

2018. 625-626.

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Harvard

APA

Vancouver

Author

Bibtex - Lataa

@conference{4cd4b188ac8b46bf90a2414cedf8f769,
title = "Towards Lazy Grounding with Lazy Normalization in Answer-Set Programming (Extended Abstract)",
abstract = "Answer-Set Programming (ASP) is an expressive rule-based knowledge-representation formalism supported by efficient solver technology. Traditional evaluation of answer-set programs takes place in two phases: grounding and solving. Grounding incurs an up-to exponential increase in space, termed the grounding bottleneck of ASP, which is often encountered in practice. Lazy grounding avoids this bottleneck but is restricted to normal rules, significantly limiting the expressive power of this approach. We propose a framework to handle aggregates by normalizing them on demand during the lazy grounding process; we call this approach lazy normalization. It is feasible for different types of aggregates and can bring about up-to exponential gains in space and time.",
keywords = "Knowledge Representation, Lazy Grounding, Normalization, Nonmonotonic Reasoning, Answer-Set Programming",
author = "Jori Bomanson and Tomi Janhunen and Antonius Weinzierl",
year = "2018",
language = "English",
pages = "625--626",

}

RIS - Lataa

TY - CONF

T1 - Towards Lazy Grounding with Lazy Normalization in Answer-Set Programming (Extended Abstract)

AU - Bomanson, Jori

AU - Janhunen, Tomi

AU - Weinzierl, Antonius

PY - 2018

Y1 - 2018

N2 - Answer-Set Programming (ASP) is an expressive rule-based knowledge-representation formalism supported by efficient solver technology. Traditional evaluation of answer-set programs takes place in two phases: grounding and solving. Grounding incurs an up-to exponential increase in space, termed the grounding bottleneck of ASP, which is often encountered in practice. Lazy grounding avoids this bottleneck but is restricted to normal rules, significantly limiting the expressive power of this approach. We propose a framework to handle aggregates by normalizing them on demand during the lazy grounding process; we call this approach lazy normalization. It is feasible for different types of aggregates and can bring about up-to exponential gains in space and time.

AB - Answer-Set Programming (ASP) is an expressive rule-based knowledge-representation formalism supported by efficient solver technology. Traditional evaluation of answer-set programs takes place in two phases: grounding and solving. Grounding incurs an up-to exponential increase in space, termed the grounding bottleneck of ASP, which is often encountered in practice. Lazy grounding avoids this bottleneck but is restricted to normal rules, significantly limiting the expressive power of this approach. We propose a framework to handle aggregates by normalizing them on demand during the lazy grounding process; we call this approach lazy normalization. It is feasible for different types of aggregates and can bring about up-to exponential gains in space and time.

KW - Knowledge Representation

KW - Lazy Grounding

KW - Normalization

KW - Nonmonotonic Reasoning

KW - Answer-Set Programming

M3 - Abstract

SP - 625

EP - 626

ER -

ID: 27477297