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..
Automated Synthesis of Mechanisms
Authors: Munyque Mittelmann, Bastien Maubert, Aniello Murano, Laurent Perrussel
IJCAI 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we show how this problem can be rephrased as a synthesis problem, where mechanisms are automatically synthesized from a partial or complete specification in a high-level logical language. We solve automated mechanism design in two cases: when the number of actions is bounded, and when agents play in turn. The paper focuses on theoretical concepts such as strategy logic, satisfiability, and decidability proofs. |
| Researcher Affiliation | Academia | Munyque Mittelmann1 , Bastien Maubert2 , Aniello Murano2 and Laurent Perrussel1 1IRIT Universit e Toulouse 1 Capitole, France 2Universit a degli Studi di Napoli Federico II , Italy |
| Pseudocode | Yes | Algorithm 1: Optimal mechanism synthesis |
| Open Source Code | No | The paper does not provide any links to open-source code or explicitly state that code for their methodology is available. |
| Open Datasets | No | The paper describes a theoretical framework and does not involve empirical studies with training datasets. Therefore, it does not provide access information for any dataset. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical studies or dataset splits for validation. Therefore, it does not specify any dataset splits. |
| Hardware Specification | No | The paper is theoretical and focuses on logic and synthesis. It does not mention any specific hardware used for running experiments or simulations. |
| Software Dependencies | No | The paper is theoretical and does not describe an experimental setup with specific software dependencies or version numbers for replication. |
| Experiment Setup | No | The paper describes a theoretical framework and an algorithm for synthesis. It does not include an experimental setup with hyperparameters or other system-level training settings. |