Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Knowing Whetherโ in Proper Epistemic Knowledge Bases
Authors: Tim Miller, Paolo Felli, Christian Muise, Adrian Pearce, Liz Sonenberg
AAAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we extend PEKBs to deal with a restricted form of disjunction: knowing whether . An agent i knows whether ฯ iff agent i knows ฯ or knows ฯ; that is, iฯ i ฯ. ...we present sound polynomial-time entailment algorithms on PEKBs with ฮi in Kn and KDn, but which are complete for a smaller class of queries than standard PEKBs. |
| Researcher Affiliation | Academia | Tim Miller, Paolo Felli, Christian Muise, Adrian R. Pearce, Liz Sonenberg Department of Computing and Information Systems, University of Melbourne EMAIL |
| Pseudocode | No | The paper contains logical definitions, theorems, and proofs but no pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any information or links to open-source code for the described methodology. |
| Open Datasets | No | This is a theoretical paper presenting logical extensions and algorithms, not empirical research involving datasets. Thus, there is no mention of training data. |
| Dataset Splits | No | This is a theoretical paper presenting logical extensions and algorithms, not empirical research involving datasets. Thus, there is no mention of validation data. |
| Hardware Specification | No | The paper is theoretical and does not describe experiments, so no hardware specifications are mentioned. |
| Software Dependencies | No | The paper is theoretical and does not describe experiments or software implementations with specific version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe experimental setups, hyperparameters, or training configurations. |