Belief Change in a Preferential Non-monotonic Framework
Authors: Giovanni Casini, Thomas Meyer
IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper we show that we can also integrate the two formalisms by studying belief change within a (preferential) non-monotonic framework. This integration relies heavily on the identification of the monotonic core of a non-monotonic framework. We consider belief change operators in a non-monotonic propositional setting with a view towards preserving consistency. These results can also be applied to the preservation of coherence an important notion within the field of logic-based ontologies. We show that the standard AGM approach to belief change can be adapted to a preferential non-monotonic framework, with the definition of expansion, contraction, and revision operators, and corresponding representation results. |
| Researcher Affiliation | Academia | Giovanni Casini Universit e du Luxembourg Luxembourg giovanni.casini@uni.lu Thomas Meyer CAIR-CSIR University of Cape Town South Africa tmeyer@cs.uct.ac.za |
| Pseudocode | No | The paper focuses on theoretical definitions, postulates, and theorems, and does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not contain any statements about releasing open-source code or provide links to a code repository. |
| Open Datasets | No | The paper is theoretical and does not involve empirical experiments with datasets, so there is no mention of training data availability. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical experiments with datasets, so there is no mention of validation splits or processes. |
| Hardware Specification | No | The paper is theoretical and does not describe any computational experiments; therefore, it does not specify any hardware used. |
| Software Dependencies | No | The paper is theoretical and does not involve implementation details or computational experiments, so it does not list any software dependencies with specific version numbers. |
| Experiment Setup | No | The paper is theoretical and focuses on formal definitions and proofs. It does not describe any practical experimental setups, hyperparameters, or training configurations. |