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].
Second-Order Quantified Boolean Logic
Authors: Jie-Hong R. Jiang
AAAI 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we investigate the second-order quantified Boolean logic with the following main results: First, we present a procedure of quantifier elimination converting SOQBFs to QBFs and a game interpretation of SOQBF semantics. Second, we devise a sound and complete refutation-proof system for SOQBF. Third, we develop an algorithm for countermodel extraction from a refutation proof. Finally, we show potential applications of SOQBFs in system design and multi-agent planning. |
| Researcher Affiliation | Academia | Jie-Hong R. Jiang Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan EMAIL |
| Pseudocode | Yes | Algorithm 1: Countermodel Extraction |
| Open Source Code | No | The paper does not provide any explicit statements about releasing source code for the described methodology, nor does it include links to a code repository. |
| Open Datasets | No | The paper is theoretical and does not conduct empirical studies using datasets for training, validation, or testing. The examples provided (Example 1, Example 2) are illustrative within the theoretical framework. |
| Dataset Splits | No | The paper is theoretical and does not conduct empirical studies. Therefore, it does not specify dataset splits for validation or other purposes. |
| Hardware Specification | No | The paper is theoretical and does not describe any empirical experiments that would require specific hardware. No hardware specifications are mentioned. |
| Software Dependencies | No | The paper is theoretical and does not describe any empirical experiments or implementations that would require specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any empirical experiments or their setup, hyperparameters, or training configurations. |