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..
Unbounded Orchestrations of Transducers for Manufacturing
Authors: Natasha Alechina, Tomáš Brázdil, Giuseppe De Giacomo, Paolo Felli, Brian Logan, Moshe Y. Vardi2646-2653
AAAI 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We model manufacturing processes and facilities as transducers (automata with output), and show that the unbounded orchestration problem is decidable and the (Pareto) optimal set of resources necessary to manufacture a product is computable for uni-transducers. However, for multi-transducers, the problem is undecidable. |
| Researcher Affiliation | Academia | Natasha Alechina University of Nottingham Nottingham, UK; Tom aˇs Br azdil Mazaryk University Brno, Czech Republic; Giuseppe De Giacomo Sapienza Universit a di Roma Roma, Italy; Paolo Felli University of Bozen-Bolzano Bolzano, Italy; Brian Logan University of Nottingham Nottingham, UK; Moshe Y. Vardi Rice University Houston, USA |
| Pseudocode | No | The paper describes theoretical constructs like transducers and energy games but does not include any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | This is a theoretical paper focused on decidability and computability; it does not involve experimental evaluation on a dataset. |
| Dataset Splits | No | This is a theoretical paper and does not involve experimental validation on dataset splits. |
| Hardware Specification | No | This is a theoretical paper and does not mention any specific hardware used for experiments. |
| Software Dependencies | No | This is a theoretical paper and does not list specific software dependencies with version numbers. |
| Experiment Setup | No | This is a theoretical paper and does not describe an experimental setup or hyperparameters. |