SMACS: A framework for formal verification of complex adaptive systems

Abstract

Abstract Self-adaptive systems (SASs) have the capability to evaluate and change their behavior according to changes occurring in the environment. Research in this field is being held since mid-60, and over the last decade, the importance of self-adaptivity is being increased. In the proposed research, colored petri nets (CPN) formal language is being used to model self-adaptive multiagent system. CPN is increasingly used to model self-adaptive complex concurrent systems due to its flexible formal specification and formal verification behavior. CPN being visually more expressive than simple, Petri Nets enable diverse modeling approaches and provides a richer framework for such a complex formalism. The main goal of this research is to apply self-adaptive multi-agent concurrent system (SMACS) for complex architectures. In our previous research, the SMACS framework is proposed and verified through traffic monitoring system. All agents of SMACS are also known as intelligent agents due to their self-adaptation behavior. Due to decentralized approach in this framework, each agent will intelligently adapt its behavior in the environment and send updates to other agents. In this research, we are choosing smart computer lab (SCL) as a case study. For internal structure of each agent modal, μ \mu -calculus will be used, and then a model checker TAPAs: a tool for the analysis of process algebras will be applied to verify these properties. CPN-based state space analysis will also be done to verify the behavioral properties of the model. The general objective of the proposed system is to maximize the utility generated over some predetermined time horizon.