On the Logic of Theory Change Iteration of KM-Update, Revised

Authors: Liangda Fang, Tong Zhu, Quanlong Guan, Junming Qiu, Zhao-Rong Lai, Weiqi Luo, Hai Wan

IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical This paper is intended to address all these shortcomings of Ferm e and Gonc alves s approach. Firstly, we present a modification of the original KM postulates based on belief states, and propose the notion of faithful collective assignments of belief states to partial preorders. Subsequently, we migrate several well-known postulates for iterated belief revision to iterated belief update. Moreover, we provide the exact semantic characterizations based on partial preorders for each of the proposed postulates. Finally, we analyze the compatibility between the above iterated postulates and the KM postulates for belief update. We identify an update operator that satisfies (CU3) and (CU4). In particular, we show that each of (CU1) and (CU2) is inconsistent with the KM postulates.
Researcher Affiliation Academia 1 Jinan University, Guangzhou 510632, China 2 Sun Yat-sen University, Guangzhou 510006, China 3 Pazhou Lab, Guangzhou 510330, China {fangld, gql}@jnu.edu.cn, zhutong62@stu2020.jnu.edu.cn, qiujm9@mail2.sysu.edu.cn
Pseudocode No The paper describes theoretical concepts and proofs, but does not include any pseudocode or algorithm blocks.
Open Source Code No The paper does not contain any statement about releasing source code or provide any links to a code repository.
Open Datasets No The paper does not mention using any datasets for training or analysis. The examples provided are illustrative scenarios, not empirical data.
Dataset Splits No The paper is theoretical and does not refer to dataset splits for training, validation, or testing.
Hardware Specification No The paper is theoretical and does not describe computational experiments or specific hardware used.
Software Dependencies No The paper is theoretical and does not describe computational experiments or specific software dependencies with version numbers.
Experiment Setup No The paper is theoretical and does not describe any experimental setup or hyperparameters.