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 Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
On Exploiting Hitting Sets for Model Reconciliation
Authors: Stylianos Loukas Vasileiou, Alessandro Previti, William Yeoh6514-6521
AAAI 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We conclude our paper with an empirical evaluation of the newly introduced approach on planning instances, where we show how it outperforms an existing stateof-the-art solver, and generic non-planning instances from recent SAT competitions, for which no other solver exists. |
| Researcher Affiliation | Collaboration | Stylianos Loukas Vasileiou,1 Alessandro Previti, 2 William Yeoh 1 1 Washington University in St. Louis 2 Ericsson Research EMAIL, EMAIL |
| Pseudocode | Yes | Algorithm 1: Basic algorithm for computing the smallest support (one KB) |
| Open Source Code | Yes | The code repository is: https://github.com/vstylianos/aaai21. |
| Open Datasets | Yes | We used the actual IPC instances as the model of the agent (i.e., KBa)... |
| Dataset Splits | No | The paper mentions using 'IPC instances' and 'SAT competition instances' but does not specify any training, validation, or test dataset splits, percentages, or methodology for data partitioning. |
| Hardware Specification | Yes | We ran our experiments on a Mac Book Pro machine comprising of an Intel Core i7 2.6GHz processor with 16GB of memory. |
| Software Dependencies | No | Our implementation of Algorithm 2 is written in Python and integrates calls to SAT, MCS/MUS, and minimal hitting set oracles through the Py SAT toolkit (Ignatiev, Morgado, and Marques-Silva 2018). |
| Experiment Setup | Yes | The time limit was set to 1500s. |