Modeling and Simulating Adaptive Multi-agent Systems with CAMLE

Abstract

Abstract-With the advent of embedded and mobile computing techniques, software systems are increasingly operated in open and dynamic environments. Such systems desire self-adaptive capabilities. This paper proposes an agent-oriented approach to the modeling and simulation of distributed adaptive systems. The approach enables the designers to construct structural and behavioral models at a high abstraction level, and to validate the models at design stage through simulation. The modeling language supports devising decentralized adaption logic that enables various types of adaptions at both component and system levels. The simulation of adaptation processes can demonstrate how a system dynamically re-organizes in response to the changes in the operating context. Case studies show that our approach can support various self-adaptation mechanisms in which a multi-agent system adapts to internal failures, unexpected environment, or user's changing requirements.

CIDE: An Integrated Development Environment for Microservices

“…Therefore, as shown in Figure 2, we integrated into CIDE a tool for constructing graphic models of systems in a modelling language called CAMLE. We also integrated Figure 2 Architecture of CIDE tools for checking model consistency and completeness, for transforming CAMLE models into formal specifications in SLABS [9,10,11], for editing formal specification of multiagent systems in SLABS [12], and for automatically transforming formal specifications in SLABS into CAOPLE source code skeletons. Such tools help to reduce the complexity of programming by modelling system structure with graphic models.…”

Formal Modelling of Real-Time Self-Adaptive Multi-Agent Systems

“…Their approach is based on dynamic heuristics for the systems learning process. Self-adaptive multi-agent system's and their interaction has been discussed in [79,80]. [81][82][83][84][85][86][87][88] has presented an in depth analysis of the challenges, application and approaches of self-adaptive systems.…”