Model checking of multi-agent systems (MAS) is known to be hard, both theoretically and in practice. A smart abstraction of the state space may significantly reduce the model, and facilitate the verification. In this paper, we propose and study an intuitive agent-based abstraction scheme, based on the removal of variables in the representation of a MAS. This allows to do the reduction without generating the global model of the system. Moreover, the process is easy to understand and control even for domain experts with little knowledge of computer science. We formally prove the correctness of the approach, and evaluate the gains experimentally on models of a postal voting procedure.
翻译:已知多试剂系统模型检查在理论上和实践上都是困难的,明智地抽取国家空间可能大大减少模型,并便利核查。在本文件中,我们提出并研究一个直觉的代理抽取计划,其基础是删除MAS代表的变量,这样可以进行削减,而不会产生系统的全球模型。此外,即使对计算机科学知之甚少的域专家来说,这一过程也是容易理解和控制的。我们正式证明了这种方法的正确性,并用邮政投票程序模型对收益进行了实验性评估。