An Axiomatic Approach to Revising Preferences
Authors: Adrian Haret, Johannes Peter Wallner5676-5683
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We study a model of preference revision in which a prior preference over a set of alternatives is adjusted... We analyze this model under two aspects: the first allows us to capture natural distance-based operators... Requiring the input and output to be aligned yields a second type of operator, which we characterize using preferences on the comparisons in the prior preference. Preference revision is set in a logic-based framework and using the formal machinery of belief change... we propose rationality postulates for each of the two versions of our model and derive representation results... |
| Researcher Affiliation | Academia | 1 Institute for Logic, Language and Computation (ILLC), University of Amsterdam, The Netherlands 2 Institute of Software Technology, Graz University of Technology, Austria |
| Pseudocode | No | The paper describes procedures like the 'addi' operator in text and with a diagram (Figure 2), but does not provide formal pseudocode blocks or algorithms. |
| Open Source Code | No | The paper does not provide any statement or link indicating the availability of open-source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and uses illustrative examples rather than empirical datasets for training. Therefore, no information on publicly available training datasets is provided. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical experiments requiring dataset splits for validation. |
| Hardware Specification | No | The paper is theoretical and does not report on computational experiments that would require specific hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not list specific software dependencies with version numbers for reproducibility of empirical experiments. |
| Experiment Setup | No | The paper is theoretical and does not describe empirical experiments with specific setup details like hyperparameters or training configurations. |