Clouseau: Generating Communication Protocols from Commitments
Authors: Munindar Singh, Amit Chopra7244-7252
AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We contribute Clouseau, an approach that takes a commitment-based speciļ¬cation 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 speciļ¬cation; (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 singh@ncsu.edu Amit K. Chopra Lancaster University Lancaster LA1 4WA, United Kingdom amit.chopra@lancaster.ac.uk |
| 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. |