Knowledge Compilation for KLM-Style Defeasible Reasoning

Luke Slater; Thomas Meyer; Jesse Heyninck

doi:10.1007/978-3-031-78255-8_29

Knowledge Compilation for KLM-Style Defeasible Reasoning

Luke Slater^*, Thomas Meyer, Jesse Heyninck

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference Article in proceeding › Academic › peer-review

Abstract

In artificial intelligence, knowledge compilation involves transforming knowledge into a form that facilitates efficient reasoning. We introduce a method for knowledge compilation of ranked interpretations within the KLM framework for defeasible reasoning. Leveraging binary decision diagrams (BDDs), a well-established tool in knowledge compilation, we demonstrate that ranked interpretations can be effectively represented using a BDD with multiple terminal nodes, termed a ranked binary decision diagram (RBDD). Additionally, we show that an existing procedure for checking entailment against a BDD can be adapted with minimal modification to check defeasible entailment against an RBDD.

Original language	English
Title of host publication	Artificial Intelligence Research - 5th Southern African Conference, SACAIR 2024, Proceedings
Editors	Aurona Gerber, Jacques Maritz, Anban W. Pillay
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	493-508
Number of pages	16
Volume	2326
ISBN (Print)	9783031782541
DOIs	https://doi.org/10.1007/978-3-031-78255-8_29
Publication status	Published - 2025
Event	5th Southern African Conference for Artificial Intelligence Research - Bloemfontein, South Africa Duration: 2 Dec 2024 → 6 Dec 2024 Conference number: 5 https://2024.sacair.org.za/

Publication series

Series	Communications in Computer and Information Science
Volume	2326 CCIS
ISSN	1865-0929

Conference

Conference	5th Southern African Conference for Artificial Intelligence Research
Abbreviated title	SACAIR 2024
Country/Territory	South Africa
City	Bloemfontein
Period	2/12/24 → 6/12/24
Internet address	https://2024.sacair.org.za/

Keywords

binary decision diagrams
defeasible reasoning
knowledge compilation
knowledge representation and reasoning
rational closure

Access to Document

10.1007/978-3-031-78255-8_29

Cite this

Slater, Luke ; Meyer, Thomas ; Heyninck, Jesse. / Knowledge Compilation for KLM-Style Defeasible Reasoning. Artificial Intelligence Research - 5th Southern African Conference, SACAIR 2024, Proceedings. editor / Aurona Gerber ; Jacques Maritz ; Anban W. Pillay. Vol. 2326 Springer Science and Business Media Deutschland GmbH, 2025. pp. 493-508 (Communications in Computer and Information Science, Vol. 2326 CCIS).

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title = "Knowledge Compilation for KLM-Style Defeasible Reasoning",

abstract = "In artificial intelligence, knowledge compilation involves transforming knowledge into a form that facilitates efficient reasoning. We introduce a method for knowledge compilation of ranked interpretations within the KLM framework for defeasible reasoning. Leveraging binary decision diagrams (BDDs), a well-established tool in knowledge compilation, we demonstrate that ranked interpretations can be effectively represented using a BDD with multiple terminal nodes, termed a ranked binary decision diagram (RBDD). Additionally, we show that an existing procedure for checking entailment against a BDD can be adapted with minimal modification to check defeasible entailment against an RBDD.",

keywords = "binary decision diagrams, defeasible reasoning, knowledge compilation, knowledge representation and reasoning, rational closure",

author = "Luke Slater and Thomas Meyer and Jesse Heyninck",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.; 5th Southern African Conference for Artificial Intelligence Research, SACAIR 2024 ; Conference date: 02-12-2024 Through 06-12-2024",

year = "2025",

doi = "10.1007/978-3-031-78255-8_29",

language = "English",

isbn = "9783031782541",

volume = "2326",

series = "Communications in Computer and Information Science",

publisher = "Springer Science and Business Media Deutschland GmbH",

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editor = "Aurona Gerber and Jacques Maritz and Pillay, {Anban W.}",

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Slater, L, Meyer, T & Heyninck, J 2025, Knowledge Compilation for KLM-Style Defeasible Reasoning. in A Gerber, J Maritz & AW Pillay (eds), Artificial Intelligence Research - 5th Southern African Conference, SACAIR 2024, Proceedings. vol. 2326, Springer Science and Business Media Deutschland GmbH, Communications in Computer and Information Science, vol. 2326 CCIS, pp. 493-508, 5th Southern African Conference for Artificial Intelligence Research, Bloemfontein, South Africa, 2/12/24. https://doi.org/10.1007/978-3-031-78255-8_29

Knowledge Compilation for KLM-Style Defeasible Reasoning. / Slater, Luke; Meyer, Thomas; Heyninck, Jesse.
Artificial Intelligence Research - 5th Southern African Conference, SACAIR 2024, Proceedings. ed. / Aurona Gerber; Jacques Maritz; Anban W. Pillay. Vol. 2326 Springer Science and Business Media Deutschland GmbH, 2025. p. 493-508 (Communications in Computer and Information Science, Vol. 2326 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference Article in proceeding › Academic › peer-review

TY - GEN

T1 - Knowledge Compilation for KLM-Style Defeasible Reasoning

AU - Slater, Luke

AU - Meyer, Thomas

AU - Heyninck, Jesse

N1 - Conference code: 5

PY - 2025

Y1 - 2025

N2 - In artificial intelligence, knowledge compilation involves transforming knowledge into a form that facilitates efficient reasoning. We introduce a method for knowledge compilation of ranked interpretations within the KLM framework for defeasible reasoning. Leveraging binary decision diagrams (BDDs), a well-established tool in knowledge compilation, we demonstrate that ranked interpretations can be effectively represented using a BDD with multiple terminal nodes, termed a ranked binary decision diagram (RBDD). Additionally, we show that an existing procedure for checking entailment against a BDD can be adapted with minimal modification to check defeasible entailment against an RBDD.

AB - In artificial intelligence, knowledge compilation involves transforming knowledge into a form that facilitates efficient reasoning. We introduce a method for knowledge compilation of ranked interpretations within the KLM framework for defeasible reasoning. Leveraging binary decision diagrams (BDDs), a well-established tool in knowledge compilation, we demonstrate that ranked interpretations can be effectively represented using a BDD with multiple terminal nodes, termed a ranked binary decision diagram (RBDD). Additionally, we show that an existing procedure for checking entailment against a BDD can be adapted with minimal modification to check defeasible entailment against an RBDD.

KW - binary decision diagrams

KW - defeasible reasoning

KW - knowledge compilation

KW - knowledge representation and reasoning

KW - rational closure

U2 - 10.1007/978-3-031-78255-8_29

DO - 10.1007/978-3-031-78255-8_29

M3 - Conference Article in proceeding

AN - SCOPUS:85211804053

SN - 9783031782541

VL - 2326

T3 - Communications in Computer and Information Science

SP - 493

EP - 508

BT - Artificial Intelligence Research - 5th Southern African Conference, SACAIR 2024, Proceedings

A2 - Gerber, Aurona

A2 - Maritz, Jacques

A2 - Pillay, Anban W.

PB - Springer Science and Business Media Deutschland GmbH

T2 - 5th Southern African Conference for Artificial Intelligence Research

Y2 - 2 December 2024 through 6 December 2024

ER -

Slater L, Meyer T, Heyninck J. Knowledge Compilation for KLM-Style Defeasible Reasoning. In Gerber A, Maritz J, Pillay AW, editors, Artificial Intelligence Research - 5th Southern African Conference, SACAIR 2024, Proceedings. Vol. 2326. Springer Science and Business Media Deutschland GmbH. 2025. p. 493-508. (Communications in Computer and Information Science, Vol. 2326 CCIS). doi: 10.1007/978-3-031-78255-8_29

Knowledge Compilation for KLM-Style Defeasible Reasoning

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