Hosny A. Abbas

Organization of Multi-Agent Systems: An Overview

In complex, open, and heterogeneous environments, agents must be able to reorganize towards the most appropriate organizations to adapt unpredictable environment changes within Multi-Agent Systems (MAS). Types of reorganization can be seen from two different levels. The individual agents level (micro-level) in which an agent changes its behaviors and interactions with other agents to adapt its local environment. And the organizational level (macro-level) in which the whole system changes it structure by adding or removing agents. This chapter is dedicated to overview different aspects of what is called MAS Organization including its motivations, paradigms, models, and techniques adopted for statically or dynamically organizing agents in MAS.

Exploiting the Overlapping of Higher Order: Entities within Multi-Agent Systems

Currently multi-agent systems (MAS, sometimes MASs) are receiving great attention as a promising approach for modeling, designing, and developing complex, decentralized and large-scale software systems. The captivating characteristics they provide such as decentralization, dynamic reorganization, self-organization, emergence, autonomy, etc., make them a perfect solution for handling current software systems challenges specially their unpredictable and highly changing working environments. Organization-centered MAS (OCMAS) are concerned with the modeling of MAS using higher order abstraction entities than individual agents. Organizational models are the key tool to develop OCMAS; they are currently an important part of most agent-oriented software engineering (AOSE) methodologies. This paper proposes a novel organizational model called NOSHAPE. It exploits the overlapping relationships among higher order abstraction entities such as organizations of agents, worlds of organizations, and even universes of worlds within MAS to realize and utilize their captivating characteristics. The NOSHAPE model is informally and semi-formally described and its applicability is demonstrated with a case study.

Realizing the NOSHAPE MAS Organizational Model: An Operational View

Dynamic reorganization of multi-agent systems MAS is currently an interesting and active research area. New emerging concepts such as self-organization and emergence are also getting great focus by MAS research community because of their captivating benefits for engineering complex large-scale MAS applications. Dynamic reorganization is considered as an effective way for building adaptive MAS. This paper provides an operational view of the conceptually proposed NOSHAPE dynamic organizational model for dynamically reorganized multi-agent systems Abbas, 2014. The operational view concerns possible design decisions, implementation issues, and suggested usage of the NOSHAPE model for practically engineering real life applications. This paper also identifies the possible solutions to be applied throughout the system design to resolve these concerns.

Towards a Hybrid MAS Organizational Model: Combining the ACMAS and OCMAS Viewpoints

Theorganizationalaspectsarecurrentlygettingagreatattentionwithinthemulti-agentsystems(MAS) community.Themotivationtowardsthistrendisfindingawaytohandletheincreasingcomplexity anddistributionofmodernagent-basedapplicationsusinghigherorderabstractionssuchasagent organizations.Itisatransitionfromconcerningthemicrolevel(individualagents)toconcerning themacrolevel(thewholesystem)tohandlecomplexity.AlargenumberofMASorganizational modelscanbefoundinMASliterature.SomeofthemadopttheACMAS(Agent-CenteredMAS) viewpointandothersadopt theOCMAS(Organizational-CenteredMAS)viewpoint.Eachof the ACMASandOCMASviewpointshasitsadvantagesanddisadvantages;therefore,combiningthem intoahybridmodelisexpectedtogiveusthechancetotakebenefitoftheiradvantagesandavoid theirdisadvantages.Thischapterpresentsourrecentworktowardstheconceptualdesignofahybrid MASorganizationalmodelthatcombinesbothoftheACMASandOCMASviewpoints. KeywORdS Hybrid Organizational Model, MAS Organization, MAS Organizational Models, Multi-Agent Systems

Self-adaptive large-scale SCADA system based on self-organised multi-agent systems

This paper provides an approach for engineering present and future large-scale supervisory control and data acquisition (SCADA) systems as a type of complex industrial networks, which are characterised by their increasing complexity and high distribution. The proposed approach adopts the emerging agent technology, which has proven to be the most representative among artificial systems dealing with complexity and high distribution. Agent-based systems that have the ability to dynamically reorganise themselves will be adaptive enough to survive within their unpredictable and highly changing environments. Adaptive agent-based systems are designed to be capable to adapt themselves to unforeseen situations in an autonomous manner. Engineering modern complex, highly distributed, and large-scale SCADA systems is currently a challenging issue and agents and multi-agent systems (MAS) can provide a feasible solution to this problem. In this paper, a self-adaptive large-scale SCADA system is designed and implemented based on dynamically organised adaptive MAS. A prototype was developed and evaluated within a simulation environment for demonstrating the effect of the transparently realised dynamic reorganisation on the system-to-be performance.