Characterizability in Belief Revision
Authors: György Turán, Jon Yaggie
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | A formal framework is given for the postulate characterizability of a class of belief revision operators, obtained from a class of partial preorders using minimization. It is shown that for classes of posets characterizability is equivalent to a special kind of definability in monadic second-order logic, which turns out to be incomparable to first-order definability. |
| Researcher Affiliation | Academia | Gy orgy Tur an University of Illinois at Chicago MTA-SZTE Research Group on Artificial Intelligence, Szeged and Jon Yaggie University of Illinois at Chicago |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not mention providing concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not involve empirical studies with datasets. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical studies or data splits. |
| Hardware Specification | No | The paper is theoretical and does not describe any experiments requiring hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not list any software dependencies with version numbers for experimental reproducibility. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup or hyperparameters. |