Conditional Independence for Iterated Belief Revision

Gabriele Kern-Isberner; J.L.A. Heyninck; Christoph Beierle

Conditional Independence for Iterated Belief Revision

Gabriele Kern-Isberner^*, J.L.A. Heyninck, Christoph Beierle

^*Corresponding author for this work

Department of Computer Science

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

Abstract

Conditional independence is a crucial concept for efficient probabilistic reasoning. For symbolic and qualitative reasoning, however, it has played only a minor role. Recently, Lynn, Delgrande, and Peppas have considered conditional independence in terms of syntactic multivalued dependencies. In this paper, we define conditional independence as a semantic property of epistemic states and present axioms for iterated belief revision operators to obey conditional independence in general. We show that c-revisions for ranking functions satisfy these axioms, and exploit the relevance of these results for iterated belief revision in general.

Original language	English
Title of host publication	Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22)
Editors	Luc De Raedt
Publisher	International Joint Conferences on Artificial Intelligence
Pages	2690-2696
Number of pages	7
ISBN (Electronic)	978-1-956792-00-3
Publication status	Published - 23 Jul 2022
Event	31st International Joint Conference on Artificial Intelligence - Messe WIen, Vienna, Austria Duration: 23 Jul 2022 → 29 Jul 2022 Conference number: 31 https://ijcai-22.org/

Conference

Conference	31st International Joint Conference on Artificial Intelligence
Abbreviated title	IJCAI-ECAI 2022
Country/Territory	Austria
City	Vienna
Period	23/07/22 → 29/07/22
Internet address	https://ijcai-22.org/

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https://www.ijcai.org/proceedings/2022/0373.pdf

Cite this

@inproceedings{c8803867615d494fa1d5fe7c8e72d312,

title = "Conditional Independence for Iterated Belief Revision",

abstract = "Conditional independence is a crucial concept for efficient probabilistic reasoning. For symbolic and qualitative reasoning, however, it has played only a minor role. Recently, Lynn, Delgrande, and Peppas have considered conditional independence in terms of syntactic multivalued dependencies. In this paper, we define conditional independence as a semantic property of epistemic states and present axioms for iterated belief revision operators to obey conditional independence in general. We show that c-revisions for ranking functions satisfy these axioms, and exploit the relevance of these results for iterated belief revision in general.",

author = "Gabriele Kern-Isberner and J.L.A. Heyninck and Christoph Beierle",

year = "2022",

month = jul,

day = "23",

language = "English",

pages = "2690--2696",

editor = "{Luc De Raedt}",

booktitle = "Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22)",

publisher = "International Joint Conferences on Artificial Intelligence",

address = "United States",

note = "31st International Joint Conference on Artificial Intelligence, IJCAI-ECAI 2022 ; Conference date: 23-07-2022 Through 29-07-2022",

url = "https://ijcai-22.org/",

}

Kern-Isberner, G, Heyninck, JLA & Beierle, C 2022, Conditional Independence for Iterated Belief Revision. in LDR (ed.), Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22). International Joint Conferences on Artificial Intelligence, pp. 2690-2696, 31st International Joint Conference on Artificial Intelligence, Vienna, Austria, 23/07/22. <https://www.ijcai.org/proceedings/2022/0373.pdf>

Conditional Independence for Iterated Belief Revision. / Kern-Isberner, Gabriele; Heyninck, J.L.A.; Beierle, Christoph.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22). ed. / Luc De Raedt. International Joint Conferences on Artificial Intelligence, 2022. p. 2690-2696.

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

TY - GEN

T1 - Conditional Independence for Iterated Belief Revision

AU - Kern-Isberner, Gabriele

AU - Heyninck, J.L.A.

AU - Beierle, Christoph

N1 - Conference code: 31

PY - 2022/7/23

Y1 - 2022/7/23

N2 - Conditional independence is a crucial concept for efficient probabilistic reasoning. For symbolic and qualitative reasoning, however, it has played only a minor role. Recently, Lynn, Delgrande, and Peppas have considered conditional independence in terms of syntactic multivalued dependencies. In this paper, we define conditional independence as a semantic property of epistemic states and present axioms for iterated belief revision operators to obey conditional independence in general. We show that c-revisions for ranking functions satisfy these axioms, and exploit the relevance of these results for iterated belief revision in general.

AB - Conditional independence is a crucial concept for efficient probabilistic reasoning. For symbolic and qualitative reasoning, however, it has played only a minor role. Recently, Lynn, Delgrande, and Peppas have considered conditional independence in terms of syntactic multivalued dependencies. In this paper, we define conditional independence as a semantic property of epistemic states and present axioms for iterated belief revision operators to obey conditional independence in general. We show that c-revisions for ranking functions satisfy these axioms, and exploit the relevance of these results for iterated belief revision in general.

UR - https://www.ijcai.org/proceedings/2022/

M3 - Conference Article in proceeding

SP - 2690

EP - 2696

BT - Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22)

A2 - , Luc De Raedt

PB - International Joint Conferences on Artificial Intelligence

T2 - 31st International Joint Conference on Artificial Intelligence

Y2 - 23 July 2022 through 29 July 2022

ER -

Conditional Independence for Iterated Belief Revision

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