Markov logic style weighted rules under the stable model semantics

Joohyung Lee; Yunsong Meng; Yi Wang

Markov logic style weighted rules under the stable model semantics

Joohyung Lee, Yunsong Meng, Yi Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We introduce the language LP^MLN that extends logic programs under the stable model semantics to allow weighted rules similar to the way Markov Logic considers weighted formulas. LP^MLN is a proper extension of the stable model semantics to enable probabilistic reasoning, providing a way to handle inconsistency in answer set programming. We also show that the recently established logical relationship between Pearl's Causal Models and answer set programs can be extended to the probabilistic setting via LP^MLN.

Original language	English (US)
Title of host publication	CEUR Workshop Proceedings
Publisher	CEUR-WS
Volume	1433
State	Published - 2015
Event	31st International Conference on Logic Programming, ICLP 2015 - Cork, Ireland Duration: Aug 31 2015 → Sep 4 2015

Other

Other	31st International Conference on Logic Programming, ICLP 2015
Country/Territory	Ireland
City	Cork
Period	8/31/15 → 9/4/15

Keywords

Answer set programming
Markov logic networks
Probabilistic causal models
Probabilistic logic programming

ASJC Scopus subject areas

Computer Science(all)

Cite this

@inproceedings{68fe3bb33ce842e882e73a80005aabfa,

title = "Markov logic style weighted rules under the stable model semantics",

abstract = "We introduce the language LPMLN that extends logic programs under the stable model semantics to allow weighted rules similar to the way Markov Logic considers weighted formulas. LPMLN is a proper extension of the stable model semantics to enable probabilistic reasoning, providing a way to handle inconsistency in answer set programming. We also show that the recently established logical relationship between Pearl's Causal Models and answer set programs can be extended to the probabilistic setting via LPMLN.",

keywords = "Answer set programming, Markov logic networks, Probabilistic causal models, Probabilistic logic programming",

author = "Joohyung Lee and Yunsong Meng and Yi Wang",

year = "2015",

language = "English (US)",

volume = "1433",

booktitle = "CEUR Workshop Proceedings",

publisher = "CEUR-WS",

note = "31st International Conference on Logic Programming, ICLP 2015 ; Conference date: 31-08-2015 Through 04-09-2015",

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T1 - Markov logic style weighted rules under the stable model semantics

AU - Lee, Joohyung

AU - Meng, Yunsong

AU - Wang, Yi

PY - 2015

Y1 - 2015

N2 - We introduce the language LPMLN that extends logic programs under the stable model semantics to allow weighted rules similar to the way Markov Logic considers weighted formulas. LPMLN is a proper extension of the stable model semantics to enable probabilistic reasoning, providing a way to handle inconsistency in answer set programming. We also show that the recently established logical relationship between Pearl's Causal Models and answer set programs can be extended to the probabilistic setting via LPMLN.

AB - We introduce the language LPMLN that extends logic programs under the stable model semantics to allow weighted rules similar to the way Markov Logic considers weighted formulas. LPMLN is a proper extension of the stable model semantics to enable probabilistic reasoning, providing a way to handle inconsistency in answer set programming. We also show that the recently established logical relationship between Pearl's Causal Models and answer set programs can be extended to the probabilistic setting via LPMLN.

KW - Answer set programming

KW - Markov logic networks

KW - Probabilistic causal models

KW - Probabilistic logic programming

UR - http://www.scopus.com/inward/record.url?scp=84944191492&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84944191492&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84944191492

VL - 1433

BT - CEUR Workshop Proceedings

PB - CEUR-WS

T2 - 31st International Conference on Logic Programming, ICLP 2015

Y2 - 31 August 2015 through 4 September 2015

ER -

Markov logic style weighted rules under the stable model semantics

Abstract

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Keywords

ASJC Scopus subject areas

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