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..
Clouseau: Generating Communication Protocols from Commitments
Authors: Munindar Singh, Amit Chopra7244-7252
AAAI 2020 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We contribute Clouseau, an approach that takes a commitment-based specification of an interaction and generates a communication protocol amenable to decentralized enactment. We show that the generated protocol is (1) correct realizes all and only the computations that satisfy the input specification; (2) safe ensures the agents local views remain consistent; and (3) live ensures the agents can proceed to completion. |
| Researcher Affiliation | Academia | Munindar P. Singh North Carolina State University Raleigh, NC 27695-8206, USA EMAIL Amit K. Chopra Lancaster University Lancaster LA1 4WA, United Kingdom EMAIL |
| Pseudocode | Yes | Algorithm 1: Protocol Generation |
| Open Source Code | No | The paper does not include an unambiguous statement about releasing code for the work described, nor does it provide a direct link to a source-code repository. |
| Open Datasets | No | The paper uses 'Net Bill' as a running example for illustrating concepts but does not report on experimental results using a dataset, nor does it provide access information for a publicly available or open dataset for training purposes. |
| Dataset Splits | No | The paper does not describe empirical experiments with data, so there is no mention of training/test/validation dataset splits. |
| Hardware Specification | No | The paper does not describe empirical experiments and therefore does not provide hardware specifications used for running experiments. |
| Software Dependencies | No | The paper does not describe empirical experiments and therefore does not provide specific software dependencies with version numbers. |
| Experiment Setup | No | The paper does not describe empirical experiments, thus no experimental setup details like hyperparameters or training settings are provided. |