Decomposing Constraint Networks for Calculating c-Representations

Authors: Marco Wilhelm, Gabriele Kern-Isberner

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Reproducibility Variable Result LLM Response
Research Type Theoretical In this paper, we focus on qualitative default reasoning based on Spohn s ranking functions for which network-based methods have not yet been studied satisfactorily. With constraint networks, we develop a framework for iterative calculations of c-representations... As an application of our framework, we show that skeptical c-inferences can be drawn locally from safe sub-bases without losing validity.
Researcher Affiliation Academia Marco Wilhelm, Gabriele Kern-Isberner Dept. of Computer Science, TU Dortmund University, Dortmund, Germany
Pseudocode Yes Algorithm 1: Calculation of c-representations on the basis of constraint networks
Open Source Code No The paper does not mention providing open-source code for the described methodology or a link to a code repository.
Open Datasets No The paper uses synthetic examples (e.g., 'ex = {δi | i [5]} with Σex = {a, b, c}') for illustration, but it does not utilize a publicly available dataset that would require access information.
Dataset Splits No The paper focuses on theoretical development and mathematical proofs; it does not involve empirical experiments with training, validation, or test dataset splits.
Hardware Specification No The paper is theoretical and does not describe any empirical experiments, therefore, no hardware specifications are mentioned.
Software Dependencies No The paper is theoretical and does not describe any empirical experiments, therefore, no specific software dependencies with version numbers are mentioned.
Experiment Setup No The paper is theoretical and focuses on algorithm design and mathematical proofs. It does not describe any empirical experimental setup details like hyperparameter values or training configurations.