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.
Online Agent Supervision in the Situation Calculus
Authors: Bita Banihashemi, Giuseppe De Giacomo, Yves Lespérance
IJCAI 2016 | Venue PDF | LLM Run Details | Input Tokens: 17,575 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 3,071 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 | The main results of this paper are (i) a formalization of the online maximally permissive supervisor, (ii) a sound and complete technique for execution of the agent as constrained by such a supervisor, and (iii) a new type of lookahead search construct that ensures nonblockingness over such online executions. |
| Researcher Affiliation | Academia | Bita Banihashemi York University Toronto, Canada EMAIL Giuseppe De Giacomo Sapienza Universit a di Roma Roma, Italy EMAIL Yves Lesp erance York University Toronto, Canada EMAIL |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. It defines logical predicates and language constructs but not procedural pseudocode. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not discuss datasets for training or their public availability. |
| Dataset Splits | No | The paper is theoretical and does not provide specific dataset split information for validation. |
| Hardware Specification | No | The paper does not provide specific hardware details used for running experiments. |
| Software Dependencies | No | The paper refers to theoretical frameworks (Situation Calculus, Con Golog) but does not provide specific ancillary software details with version numbers (e.g., libraries, solvers). |
| Experiment Setup | No | The paper is theoretical and does not provide specific experimental setup details such as hyperparameters or training configurations. |