Parameterised Verification of Data-aware Multi-Agent Systems
Authors: Francesco Belardinelli, Panagiotis Kouvaros, Alessio Lomuscio
IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We show that their parameterised verification problem is semi-decidable for classes of interest. This is demonstrated by separately addressing the unboundedness of the number of agents and the data domain. In doing so we reduce the parameterised model checking problem for these systems to that of parameterised verification for interleaved interpreted systems. |
| Researcher Affiliation | Academia | Francesco Belardinelli Laboratoire IBISC, UEVE IRIT Toulouse, France belardinelli@ibisc.fr Panagiotis Kouvaros Department of Computing Imperial College London, UK Univ. of Naples Federico II , Italy p.kouvaros@imperial.ac.uk Alessio Lomuscio Department of Computing Imperial College London, UK a.lomuscio@imperial.ac.uk |
| Pseudocode | No | The paper describes definitions and procedures using mathematical notation and descriptive text, but it does not contain a clearly labeled 'Pseudocode' or 'Algorithm' block. |
| Open Source Code | No | The paper does not provide an explicit statement about releasing source code for the described methodology, nor does it provide a link to a code repository. |
| Open Datasets | No | This paper is theoretical and focuses on formalisms for systems with 'infinite data domain' and 'unbounded number of agents'. It does not use or refer to any specific publicly available dataset for training or evaluation. |
| Dataset Splits | No | This paper is theoretical and does not involve empirical experiments with datasets. Therefore, it does not provide details on training, validation, or test dataset splits. |
| Hardware Specification | No | This paper is theoretical and does not describe empirical experiments. Therefore, it does not specify any hardware used for running experiments. |
| Software Dependencies | No | This paper is theoretical and does not describe software implementation details with specific version numbers for its methodology. It refers to 'open-source toolkits' in related work, but not for its own contribution. |
| Experiment Setup | No | This paper is theoretical and does not describe empirical experiments. Therefore, it does not provide details on experimental setup, hyperparameters, or training configurations. |