Epistemic Equilibrium Logic

Authors: Luis Fariñas del Cerro, Andreas Herzig, Ezgi Iraz Su

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

Reproducibility Variable Result LLM Response
Research Type Theoretical We add epistemic modal operators to the language of here-and-there logic and define epistemic hereand-there models. We then successively define epistemic equilibrium models and autoepistemic equilibrium models. The former are obtained from here-and-there models by the standard minimisation of truth of Pearce s equilibrium logic; they provide an epistemic extension of that logic. The latter are obtained from the former by maximising the set of epistemic possibilities; they provide a new semantics for Gelfond s epistemic specifications. For both definitions we characterise strong equivalence by means of logical equivalence in epistemic hereand-there logic.
Researcher Affiliation Academia Luis Fari nas del Cerro, Andreas Herzig and Ezgi Iraz Su University of Toulouse, CNRS, IRIT Toulouse, France http://www.irit.fr
Pseudocode No The paper does not contain any structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide concrete access to source code for the methodology described. There is no mention of a repository link, an explicit code release statement, or code in supplementary materials.
Open Datasets No The paper is theoretical and does not use or reference any datasets for training. Thus, it does not provide concrete access information for a publicly available or open dataset.
Dataset Splits No The paper does not involve empirical experiments with datasets, and therefore does not provide specific dataset split information for validation.
Hardware Specification No The paper is theoretical and does not describe any computational experiments, thus no specific hardware details are provided for running experiments.
Software Dependencies No The paper is theoretical and does not describe any software implementations, thus no specific ancillary software details with version numbers are provided.
Experiment Setup No The paper is theoretical and does not describe any empirical experiments, thus no specific experimental setup details like hyperparameters or training configurations are provided.