Synthesis of Orchestrations of Transducers for Manufacturing

Authors: Giuseppe De Giacomo, Moshe Vardi, Paolo Felli, Natasha Alechina, Brian Logan

AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical In this paper, we model manufacturing processes and facilities as transducers (automata with output). ... We show that synthesizing orchestrations for uni-transducers is EXPTIME-complete. Surprisingly, the complexity remains the same for the more expressive multi-transducer case... Technically our problem is a significant extension of behavior and service composition... Instead, we resort to game theoretic techniques used in LTL reactive synthesis... Our aim in this work is to automate manual process planning; as such we have not addressed the quantitative aspects of production.
Researcher Affiliation Academia Giuseppe De Giacomo Sapienza Universit a di Roma, Italy degiacomo@dis.uniroma1.it Moshe Y. Vardi Rice University, Houston, USA vardi@cs.rice.edu Paolo Felli Univ. of Bozen-Bolzano, Bolzano, Italy pfelli@unibz.it Natasha Alechina University of Nottingham, UK nza@cs.nott.ac.uk Brian Logan University of Nottingham, UK bsl@cs.nott.ac.uk
Pseudocode No The paper describes algorithms and mathematical formulations but does not include structured pseudocode blocks or sections explicitly labeled "Algorithm".
Open Source Code No The paper does not provide any information or links regarding the availability of open-source code for the described methodology.
Open Datasets No The paper uses illustrative examples (e.g., Example 1, Example 3) to demonstrate the concepts, but it does not use or provide access information for any publicly available or open datasets for empirical evaluation.
Dataset Splits No The paper is theoretical and does not describe empirical experiments with datasets, thus no training/validation/test splits are provided.
Hardware Specification No The paper is theoretical and focuses on models and algorithms; it does not describe any specific hardware used for experiments.
Software Dependencies No The paper describes theoretical models and algorithms but does not specify any software dependencies or version numbers needed for replication.
Experiment Setup No The paper is theoretical and does not describe empirical experiments, therefore no experimental setup details like hyperparameters or training configurations are provided.