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].
Epistemic Quantified Boolean Logic: Expressiveness and Completeness Results
Authors: Francesco Belardinelli, Wiebe van der Hoek
IJCAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We introduce epistemic quantified boolean logic (EQBL), an extension of propositional epistemic logic with quantification over propositions. We show that EQBL can express relevant properties about agents knowledge in multi-agent contexts, such as agent a knows as much as agent b . We analyse the expressiveness of EQBL through a translation into monadic second-order logic, and provide completeness results w.r.t. various classes of Kripke frames. Finally, we prove that model checking EQBL is PSPACE-complete. |
| Researcher Affiliation | Academia | Francesco Belardinelli Laboratoire IBISC, Universit e d Evry, France EMAIL Wiebe van der Hoek Department of Computer Science University of Liverpool, UK EMAIL |
| Pseudocode | Yes | Algorithm 1 Computation of the satisfaction set [[φ]]M switch (φ): case : return ; case p: return V (p); case ψ: return W \ [[ψ]]M; case ψ ψ : return [[ψ]]M [[ψ ]]M; case Kaψ: return {w W | Ra(w) [[ψ]]M}; case Cψ: return {w W | (S a Ag Ra) (w) [[ψ]]M}; case pψ: return T U D{[[ψ]]M ) | M = F, V p U }; |
| Open Source Code | No | The paper does not provide any explicit statement about releasing source code for the described methodology or links to a code repository. |
| Open Datasets | No | The paper is theoretical and does not involve empirical experiments with datasets. The card game example is illustrative, not a dataset used for training or evaluation. |
| Dataset Splits | No | The paper does not conduct empirical experiments, and therefore no training, validation, or test dataset splits are provided. |
| Hardware Specification | No | The paper is theoretical, focusing on logic, expressiveness, completeness, and complexity analysis. It does not describe any experiments that would require specific hardware specifications. |
| Software Dependencies | No | The paper is theoretical and describes a formal logic. There are no mentions of specific software libraries, frameworks, or tools with version numbers that would be required for reproducibility. |
| Experiment Setup | No | The paper is theoretical and does not describe any empirical experiments, thus no experimental setup details, hyperparameters, or training configurations are provided. |