Notice: This website is continuously updated as new conference proceedings and journal volumes are published. Consequently, the figures presented here may differ from those reported in our publications.
A brief overview of our methodology is provided on the Methods page, along with references to publications documenting our approach and links to the code and data used in each study.
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.
A Tractable, Expressive, and Eventually Complete First-Order Logic of Limited Belief
Authors: Gerhard Lakemeyer, Hector J. Levesque
IJCAI 2019 | Venue PDF | LLM Run Details | Input Tokens: 18,771 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 2,030 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we propose a novel logic of limited belief, which has all three desired properties. |
| Researcher Affiliation | Academia | Gerhard Lakemeyer1 and Hector J. Levesque2 1 Dept. of Computer Science, RWTH Aachen University, Germany 2 Dept. of Computer Science, University of Toronto, Canada |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. It provides formal definitions and proofs. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper focuses on theoretical development and does not use datasets for training, validation, or testing. |
| Dataset Splits | No | The paper focuses on theoretical development and does not use datasets for training, validation, or testing. |
| Hardware Specification | No | The paper describes theoretical work and does not mention any specific hardware used for experiments. |
| Software Dependencies | No | The paper describes theoretical work and does not mention any specific software dependencies with version numbers. |
| Experiment Setup | No | The paper describes theoretical work and does not mention any experimental setup details such as hyperparameters or training configurations. |