The Logic of Qualitative Probability

Authors: James Delgrande, Bryan Renne

IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical In this paper we present a theory of qualitative probability. ... We provide a sound and complete axiomatisation for this operator over finite outcome sets, and show that this theory is sufficiently powerful to capture the results of axiomatic probability theory.
Researcher Affiliation Academia James P. Delgrande School of Computing Science Simon Fraser University Burnaby, B.C., V5A 1S6 Canada jim@cs.sfu.ca Bryan Renne Vancouver, B.C., Canada bryan@renne.org
Pseudocode No The paper focuses on axiomatic theory and proofs, and does not include pseudocode or algorithm blocks.
Open Source Code No The paper does not mention or provide any links to open-source code for the described methodology.
Open Datasets No The paper is theoretical and does not use or reference any datasets for training or evaluation.
Dataset Splits No The paper is theoretical and does not involve experimental data splits such as validation sets.
Hardware Specification No The paper is theoretical and does not describe any experimental setup or hardware used.
Software Dependencies No The paper is theoretical and does not mention any specific software dependencies with version numbers for experimental reproducibility.
Experiment Setup No The paper is theoretical and does not describe an experimental setup, hyperparameters, or training configurations.