Composing and Verifying Commitment-Based Multiagent Protocols
Authors: Matteo Baldoni, Cristina Baroglio, Amit K. Chopra, Munindar P. Singh
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We consider the design and enactment of multiagent protocols that describe collaboration using normative or social abstractions, specifically, commitments. A (multiagent) protocol defines the relevant social states and how they progress; each participant maintains a local projection of these states and acts accordingly. Protocols expose two important challenges: (1) how to compose them in a way that respects commitments and (2) how to verify the compliance of the parties with the social states. Individually, these challenges are inadequately studied and together not at all. We motivate the notion of a social context to capture how a protocol may be enacted. A protocol can be verifiably enacted when its participants can determine each other s compliance. We first show the negative result that even when protocols can be verifiably enacted in respective social contexts, their composition cannot be verifiably enacted in the composition of those social contexts. We next show how to expand such a protocol so that it can be verifiably enacted. Our approach involves design rules to specify composite protocols so they would be verifiably enactable. Our approach demonstrates a use of dialectical commitments, which have previously been overlooked in the protocols literature. |
| Researcher Affiliation | Academia | Matteo Baldoni Universit a di Torino Torino, Italy baldoni@di.unito.it Cristina Baroglio Universit a di Torino Torino, Italy baroglio@di.unito.it Amit K. Chopra Lancaster University Lancaster, UK akchopra.mail@gmail.com Munindar P. Singh NC State University Raleigh, NC, USA singh@ncsu.edu |
| Pseudocode | Yes | Algorithm 1 Enactment Closure under Claim |
| Open Source Code | No | The paper does not contain any explicit statements about releasing source code for the methodology described, nor does it provide a direct link to a code repository. |
| Open Datasets | No | The paper is theoretical and does not conduct experiments on datasets, thus no information on public dataset availability for training is provided. |
| Dataset Splits | No | The paper is theoretical and does not conduct experiments with datasets, thus no information on dataset splits for validation is provided. |
| Hardware Specification | No | The paper is theoretical and does not report on computational experiments that would require specific hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not detail any specific software dependencies with version numbers for experimental reproducibility. |
| Experiment Setup | No | The paper is theoretical and does not describe an empirical experimental setup, including hyperparameters or system-level training settings. |