Reduction Model Checking for Multi-Agent Systems of Group Social Commitments

Innumerable industries now use multi-agent systems (MASs) in various contexts, including healthcare, security, and commercial deployments. It is challenging to select reliable business protocols for critically important safety-related systems (e.g., in healthcare). The verification and validation of business applications is increasingly explored concerning multi-agent systems? group social commitments. This study explains a novel extended reduction verification method to modelcheck business applications? critical specification rules using action restricted computation tree logic (ARCTL). In particular, we aim to conduct the verification process for the CTLGC logic using a reduction algorithm and show its effectiveness to handle MASs with huge models, thus, showing its importance and applicability in large real-world applications. To do so, we need to transform the CTLGC model to an ARCTL model and the CTLGC formulas into ARCTL formulas. Thus, the developed method was verified with the model-checker new symbolic model verifier (NuSMV), and it demonstrated effectiveness in the safety-critical specification rule support provision. The proposed method can verify up to 2.43462 ? 1014 states MASs, which shows its effectiveness when applied to real-world applications.