Developing multiagent systems: The Gaia methodology
ACM Transactions on Software Engineering and Methodology (TOSEM)
A UML Based Approach for Modeling and Implementing Multi-Agent Systems
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Proceedings of the Fifth International Conference on Security of Information and Networks
Organizational Security Architecture for Critical Infrastructure
ARES '13 Proceedings of the 2013 International Conference on Availability, Reliability and Security
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SCADA systems are urged to face more and more complex critical situation and thereby, need to continuously evolve towards integrated decision making capability driven by fancy reaction strategy. The current research stream in that field, aims, accordingly, to foster the smartness of the field equipment and actuators, which predominately exist under the concept of agents. Those agents are governed by policies that while dictating the agent behavior, depending on the agent roles and the context of evolution, also confer to the latter the latitude to react based on their own perception of the evolving environment. This agent ability is referring to as the agent smartness and is strongly determined by, and depending on, the trust perceived by the agent of its environment. Actual work related to agents tends to consider that agents evolve and are organized in systems. There exist some models for representing how these agents are organized at a high level, models for representing how they are spread in the networks, models to represent how they communicate to each other, and so forth. However, as far as we know, no model exists that integrates all of the above models. Therefore, we do believe that such an integrated model could have many advantages like e.g. to know the impact from the action from one layer to another, to decide which action on a component has the most important impact on a set of other components, to identify the most critical component for an infrastructure, to align the agent system with the corporate objective and to tailor it accordingly. Therefore, we have decided to frame an innovative version of ArchiMate® for the multi-agent purpose with the objective to enrich the agent society collaborations and, more particularly, the description of the agent behavior endorsed in the policy component and using a reputation based trust model to improve the reliability, termed ARMAN. Our work has been illustrated in the frame of a critical infrastructure in the field of electrical power distribution which is a highly sensitive research topic.