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..
Synthesizing strategies under expected and exceptional environment behaviors
Authors: Benjamin Aminof, Giuseppe De Giacomo, Alessio Lomuscio, Aniello Murano, Sasha Rubin
IJCAI 2020 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We formalize these concepts in the context of linear-temporal logic, and give an algorithm for solving this problem. We also show that there is no trade-off between enforcing the goal under the expected environment specification and making a best-effort for it under the exceptional one. |
| Researcher Affiliation | Academia | Benjamin Aminof1 , Giuseppe De Giacomo2 , Alessio Lomuscio3 , Aniello Murano4 and Sasha Rubin5 1 TU Vienna, Austria, 2 University of Rome La Sapienza , Italy, 3 Imperial College London, UK, 4 University of Naples Federico II , Italy, 5 University of Sydney, Australia |
| Pseudocode | No | The paper describes algorithms verbally but does not include any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not mention providing open-source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not use datasets for empirical studies. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical validation with training/test/validation splits. |
| Hardware Specification | No | The paper is theoretical and does not describe experiments that would require specific hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not list specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup with hyperparameters or system-level training settings. |