On uniform belief revision

被引:6
|
作者
Aravanis, Theofanis [1 ]
机构
[1] Univ Patras, Sch Econ & Business, Dept Business Adm, Patras 26500, Greece
关键词
Belief change; parametrized-difference revision; total preorders; iteration; relevance; kinetic consistency; knowledge representation; KNOWLEDGE-BASE REVISION; RELEVANCE; LOGIC;
D O I
10.1093/logcom/exaa058
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Rational belief-change policies are encoded in the so-called AGM revision functions, defined in the prominent work of AlchourrOn, Gardenfors and Makinson. The present article studies an interesting class of well-behaved AGM revision functions, called herein uniform-revision operators (or UR operators, for short). Each UR operator is uniquely defined by means of a single total preorder over all possible worlds, a fact that in turn entails a significantly lower representational cost, relative to an arbitrary AGM revision function, and an embedded solution to the iterated-revision problem, at no extra representational cost. Herein, we first demonstrate how weaker, more expressive-yet, more representationally expensive types of uniform revision can be defined. Furthermore, we prove that UR operators, essentially, generalize a significant type of belief change, namely, parametrized-difference revision. Lastly, we show that they are (to some extent) relevance-sensitive, as well as that they respect the so-called principle of kinetic consistency.
引用
收藏
页码:1357 / 1376
页数:20
相关论文
共 50 条
  • [41] Trust as a Precursor to Belief Revision
    Booth, Richard
    Hunter, Aaron
    JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 2018, 61 : 699 - 722
  • [42] Back to Basics: Belief Revision Through Direct Selection
    Hansson, Sven Ove
    STUDIA LOGICA, 2019, 107 (05) : 887 - 915
  • [43] Semantics for Containment Belief Revision in the Case of Consistent Complete Theories
    Doukari, Omar
    STAIRS 2008, 2008, 179 : 59 - 69
  • [44] Predictive Modelling of Human Reasoning Using AGM Belief Revision
    Baker, Clayton
    PROCEEDINGS OF THE THIRTY-SECOND INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, IJCAI 2023, 2023, : 7073 - 7074
  • [45] BRL: A Toolkit for Learning How an Agent Performs Belief Revision
    Hunter, Aaron
    Boyarinov, Konstantin
    ICAART: PROCEEDINGS OF THE 14TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE - VOL 3, 2022, : 753 - 756
  • [46] Filtered Belief Revision: Syntax and Semantics
    Bonanno, Giacomo
    JOURNAL OF LOGIC LANGUAGE AND INFORMATION, 2022, 31 (04) : 645 - 675
  • [47] Kinetic Consistency and Relevance in Belief Revision
    Peppas, Pavlos
    Williams, Mary-Anne
    LOGICS IN ARTIFICIAL INTELLIGENCE, (JELIA 2016), 2016, 10021 : 401 - 414
  • [48] A Unifying Framework for Probabilistic Belief Revision
    Zhuang, Zhiqiang
    Delgrande, James
    Nayak, Abhaya
    Sattar, Abdul
    PROCEEDINGS OF THE TWENTY-SIXTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2017, : 1370 - 1376
  • [49] Revising the Elenchus via Belief Revision
    Kubyshkina, Ekaterina
    Petrolo, Mattia
    LOGICA UNIVERSALIS, 2023, 17 (02) : 231 - 258
  • [50] Toward credible belief base revision
    Ktari, Raida
    Boujelben, Mohamed Ayman
    Wurbel, Eric
    INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 2023, 162