A polynomial-time predicate-logic hypothetical reasoning by networked bubble propagation method

Yukio Ohsawa, Mitsuru Ishizuka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Hypothetical reasoning is a useful knowledge-processing framework applicable to many problems including system diagnosis, design, etc. However, due to its non-monotonic inference nature, it takes exponential computation-time to find a solution hypotheses-set to prove a given goal. This is also true for cost-based hypothetical reasoning to find an optimal solution with minimal cost. As for the hypothetical reasoning expressed in propositional logic, since it is easily transformed into 0-I integer programming problem, a polynomial-time method finding a near-optimal solution has been developed so far by employing an approximate solution method of 0-1 integer programming called the Pivot and Complement method. Also, by reforming this method, a network-based inference mechanism called Networked Bubble Propagation (NBP) has been invented by the authors, which allows even faster inference. More importantly, a network-based approach is meaningful, for its potential of being developed extending to a broader framework of knowledge processing. In this paper, we extend the NBP method to dealing with the hypothetical reasoning expressed with predicate logic. By constructing a series of knowledge networks, to which the NBP method is applied, in a stepwise manner according to a top-clown control, we avoid the excessive expansion of the network size. As a result, we can achieve a polynomial time inference for computing a hoax-optimal solution for the cost-based hypothetical reasoning in predicate-logic knowledge.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages375-387
Number of pages13
Volume1081
ISBN (Print)3540612912, 9783540612919
DOIs
Publication statusPublished - 1996
Externally publishedYes
Event11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 1996 - Toronto, Canada
Duration: 1996 May 211996 May 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1081
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 1996
CountryCanada
CityToronto
Period96/5/2196/5/24

Fingerprint

Predicate Logic
Bubble
Polynomial time
Reasoning
Polynomials
Integer programming
Propagation
Costs
Optimal Solution
Reforming reactions
Processing
0-1 Integer Programming
Pivot
Propositional Logic
Integer Programming
Approximate Solution
Complement
Series
Knowledge
Computing

Keywords

  • Knowledge representation
  • Reasoning (abduction)
  • Search

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Ohsawa, Y., & Ishizuka, M. (1996). A polynomial-time predicate-logic hypothetical reasoning by networked bubble propagation method. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1081, pp. 375-387). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1081). Springer Verlag. https://doi.org/10.1007/3-540-61291-2_66

A polynomial-time predicate-logic hypothetical reasoning by networked bubble propagation method. / Ohsawa, Yukio; Ishizuka, Mitsuru.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1081 Springer Verlag, 1996. p. 375-387 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1081).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ohsawa, Y & Ishizuka, M 1996, A polynomial-time predicate-logic hypothetical reasoning by networked bubble propagation method. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 1081, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1081, Springer Verlag, pp. 375-387, 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 1996, Toronto, Canada, 96/5/21. https://doi.org/10.1007/3-540-61291-2_66
Ohsawa Y, Ishizuka M. A polynomial-time predicate-logic hypothetical reasoning by networked bubble propagation method. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1081. Springer Verlag. 1996. p. 375-387. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/3-540-61291-2_66
Ohsawa, Yukio ; Ishizuka, Mitsuru. / A polynomial-time predicate-logic hypothetical reasoning by networked bubble propagation method. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1081 Springer Verlag, 1996. pp. 375-387 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{912782f6a22248f7968f02af3e7b8b10,
title = "A polynomial-time predicate-logic hypothetical reasoning by networked bubble propagation method",
abstract = "Hypothetical reasoning is a useful knowledge-processing framework applicable to many problems including system diagnosis, design, etc. However, due to its non-monotonic inference nature, it takes exponential computation-time to find a solution hypotheses-set to prove a given goal. This is also true for cost-based hypothetical reasoning to find an optimal solution with minimal cost. As for the hypothetical reasoning expressed in propositional logic, since it is easily transformed into 0-I integer programming problem, a polynomial-time method finding a near-optimal solution has been developed so far by employing an approximate solution method of 0-1 integer programming called the Pivot and Complement method. Also, by reforming this method, a network-based inference mechanism called Networked Bubble Propagation (NBP) has been invented by the authors, which allows even faster inference. More importantly, a network-based approach is meaningful, for its potential of being developed extending to a broader framework of knowledge processing. In this paper, we extend the NBP method to dealing with the hypothetical reasoning expressed with predicate logic. By constructing a series of knowledge networks, to which the NBP method is applied, in a stepwise manner according to a top-clown control, we avoid the excessive expansion of the network size. As a result, we can achieve a polynomial time inference for computing a hoax-optimal solution for the cost-based hypothetical reasoning in predicate-logic knowledge.",
keywords = "Knowledge representation, Reasoning (abduction), Search",
author = "Yukio Ohsawa and Mitsuru Ishizuka",
year = "1996",
doi = "10.1007/3-540-61291-2_66",
language = "English",
isbn = "3540612912",
volume = "1081",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "375--387",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - A polynomial-time predicate-logic hypothetical reasoning by networked bubble propagation method

AU - Ohsawa, Yukio

AU - Ishizuka, Mitsuru

PY - 1996

Y1 - 1996

N2 - Hypothetical reasoning is a useful knowledge-processing framework applicable to many problems including system diagnosis, design, etc. However, due to its non-monotonic inference nature, it takes exponential computation-time to find a solution hypotheses-set to prove a given goal. This is also true for cost-based hypothetical reasoning to find an optimal solution with minimal cost. As for the hypothetical reasoning expressed in propositional logic, since it is easily transformed into 0-I integer programming problem, a polynomial-time method finding a near-optimal solution has been developed so far by employing an approximate solution method of 0-1 integer programming called the Pivot and Complement method. Also, by reforming this method, a network-based inference mechanism called Networked Bubble Propagation (NBP) has been invented by the authors, which allows even faster inference. More importantly, a network-based approach is meaningful, for its potential of being developed extending to a broader framework of knowledge processing. In this paper, we extend the NBP method to dealing with the hypothetical reasoning expressed with predicate logic. By constructing a series of knowledge networks, to which the NBP method is applied, in a stepwise manner according to a top-clown control, we avoid the excessive expansion of the network size. As a result, we can achieve a polynomial time inference for computing a hoax-optimal solution for the cost-based hypothetical reasoning in predicate-logic knowledge.

AB - Hypothetical reasoning is a useful knowledge-processing framework applicable to many problems including system diagnosis, design, etc. However, due to its non-monotonic inference nature, it takes exponential computation-time to find a solution hypotheses-set to prove a given goal. This is also true for cost-based hypothetical reasoning to find an optimal solution with minimal cost. As for the hypothetical reasoning expressed in propositional logic, since it is easily transformed into 0-I integer programming problem, a polynomial-time method finding a near-optimal solution has been developed so far by employing an approximate solution method of 0-1 integer programming called the Pivot and Complement method. Also, by reforming this method, a network-based inference mechanism called Networked Bubble Propagation (NBP) has been invented by the authors, which allows even faster inference. More importantly, a network-based approach is meaningful, for its potential of being developed extending to a broader framework of knowledge processing. In this paper, we extend the NBP method to dealing with the hypothetical reasoning expressed with predicate logic. By constructing a series of knowledge networks, to which the NBP method is applied, in a stepwise manner according to a top-clown control, we avoid the excessive expansion of the network size. As a result, we can achieve a polynomial time inference for computing a hoax-optimal solution for the cost-based hypothetical reasoning in predicate-logic knowledge.

KW - Knowledge representation

KW - Reasoning (abduction)

KW - Search

UR - http://www.scopus.com/inward/record.url?scp=0042743350&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0042743350&partnerID=8YFLogxK

U2 - 10.1007/3-540-61291-2_66

DO - 10.1007/3-540-61291-2_66

M3 - Conference contribution

AN - SCOPUS:0042743350

SN - 3540612912

SN - 9783540612919

VL - 1081

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 375

EP - 387

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

PB - Springer Verlag

ER -