Engineering Applications of Artificial Intelligence 24 (2011) 1095–1097

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Engineering Applications of Artificial Intelligence

0952-19

doi:10.1

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journal homepage: www.elsevier.com/locate/engappai

Infrastructures and tools for multiagent systems for the new generationof distributed systems

Ana Garcia-Fornes a,�, Jomi F. Hubner b, Andrea Omicini c, Juan A. Rodriguez-Aguilar d, Vicent Botti a

a Departament de Sistemes Inform�atics i Computacio, Universitat Polit�ecnica de Val�encia, Camı de Vera s/n, Val�encia, Spainb Department of Automation and System Engineering, Federal University of Santa Catarina, PO Box 476, Florianopolis, SC, 88040-900, Brazilc Dipartimento di Elettronica, Informatica, Sistemistica, Universit�a di Bologna, Via Venezia, 52 Cesena, Italyd IIIA-CSIC, Campus de la UAB, E-08193 Bellaterra, Catalonia, Spain

a r t i c l e i n f o

Available online 20 July 2011

Keywords:

Multiagent systems

Infrastructures

Tools

Agent platforms

Management

Security

Simulation

Industry

76/$ - see front matter & 2011 Elsevier Ltd. A

016/j.engappai.2011.06.012

esponding author.

ail addresses: agarcia@dsic.upv.es (A. Garcia-F

as.ufsc.br (J.F. Hubner), andrea.omicini@unibo

.csic.es (J.A. Rodriguez-Aguilar), vbotti@dsic.u

a b s t r a c t

In order for multiagent systems to be included in real domains (media and Internet, logistics,

e-commerce, and health care), infrastructures and tools for multiagent systems should provide

efficiency, scalability, security, management, monitoring, and other features related to building real

applications. Thus, infrastructures and tools that support multiagent systems are needed, especially

those that promote the adoption of agent-based systems by designers and programmers in both

academia and industry. This special issue is a selection of contributions whose preliminary versions

were presented at the ITMAS 2010 workshop, which was held in conjunction with the International

Conference on Autonomous Agents and Multi-agent Systems.

& 2011 Elsevier Ltd. All rights reserved.

Nowadays, technological evolution in the areas of ComputerTechnology and Communications (Internet, WWW, e-commerce,wireless connectivity, virtual worlds, etc.) has made InformationTechnology research and development focus on solving chal-lenges in order to develop distributed applications. Distributedsystems are increasingly viewed as collections of service-providerand service-consumer components that are interlinked by dyna-mically defined workflows.

However, the biggest impact of this focus has been on the wayapplications are thought of and developed. Current applicationsrequire built-in components to which more and more complextasks can be delegated. These components show higher levels ofintelligence, are capable of sophisticated ways of interacting sincethey are massively distributed, and are quite often embedded inall sorts of appliances and sensors. These autonomous compo-nents are usually referenced to as agents in order to emphasizetheir capability to represent human interests, and to be autono-mous and socially aware.

This technological evolution of the new generation of distrib-uted systems has given rise to new computation paradigmssuch as:

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peer-to-peer technologies,

ll rights reserved.

ornes),

.it (A. Omicini),

pv.es (V. Botti).

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grid computing, � autonomic computing, � computation as interaction.

With these new paradigms, it is becoming increasingly naturalto view large systems in terms of the services that they offer and,consequently, in terms of the entities or agents that provide orconsume services. In a vast amount of the literature, multiagentsystems have been selected as a proper paradigm for complexdistributed systems. In this new paradigm, computation is some-thing that occurs by means of and through communication amongcomputational entities. Instead of being a solitary activity,computation becomes an inherently social one, leading to newways of conceiving, designing, developing, and handling compu-tational systems (Sierra et al., 2011).

An example of the influence of this point of view is theemerging model of software as a service, as in the service-oriented architectures. In this model, applications are no longermonolithic, single-user applications or distributed applicationsmanaged by only one organization. Instead, they are societies ofcomputational entities (components) that can be considered asservice providers; they may enter or abandon different societiesat different times and for different reasons; and they may formcoalitions or virtual organizations among themselves to attaintheir current goals. Services should be provided by concreteentities or agents that send and receive messages, whereas theservices themselves are the resources characterized by the func-tionality that is provided.

A. Garcia-Fornes et al. / Engineering Applications of Artificial Intelligence 24 (2011) 1095–10971096

Interconnection and distribution, coupled with the need forsystems to represent our best interests, require systems that cancooperate and reach agreements (or even compete) with othersystems that have different interests (much as we do with otherpeople) (Sierra et al., 2011).

These emerging domains and environments are open anddynamic so that new agents may join and existing ones mayleave. Agents act on behalf of service owners, managing accessto services, and ensuring that contracts are fulfilled. Agentsact on behalf of service consumers, locating services, makingcontracts, and receiving and presenting results. Agents arerequired to engage in interactions, negotiate with one another,make agreements, and make proactive run-time decisions, indi-vidually and collectively, while responding to changing circum-stances. Agents need to collaborate and to form coalitions ofagents with different capabilities in support of new virtualorganizations. Therefore, we need models, frameworks, methodsand algorithms to construct large-scale open distributed compu-ter systems. The next generation of computing systems requiresthe following:

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Autonomy, interaction, and mobility as key features. Theyhave to cope with the (high) dynamism of the system topologyand with semantic mismatches in the interaction. These areboth natural consequences of the distributed and autonomousnature of the components. � Security mechanisms and trust measures that complement the

classical cryptographic methods. Trust measures are essentialin open environments where interactions have to be madeunder uncertainty of the environment state.

� Techniques that enable software components to reach agree-

ments on the mutual performance of services.

� Negotiation, argumentation, decision-making, knowledge

modeling, virtual organizations and learning. These will bethe sandbox techniques used to build this next generation ofsoftware systems.

� Software engineering methodologies that deal with the issues

raised in these new application scenarios (Giret et al., 2005;Botti et al., 2008).

When developing applications based on the new generationof distributed systems, developers and users require infrastruc-tures and tools that support essential features in multiagentsystems (such as agent organizations, mobility, etc.) and thatfacilitate the system design, management, execution, and evalua-tion (Denti et al., 2002). Agent infrastructures are usually builtusing other technologies such as grid systems, service-orientedarchitectures, P2P networks, etc. In this sense, the integrationand interoperability of such technologies in multiagent systems isalso a challenging issue in the area of both tools and infrastruc-tures for multiagent systems. A long-term goal is the industrialdevelopment of infrastructures for building highly scalable appli-cations comprising pre-existing agents that must be organized ororchestrated.

In order for multiagent systems to be included in the realdomains (media and Internet, logistics, e-commerce, and healthcare), infrastructures and tools for multiagent systems shouldprovide efficiency, scalability, security, management, monitoringand other features related to building real applications.

We need new infrastructures and tools to provide support formultiagent systems. We are particularly interested in infrastruc-tures and tools that allow agent-based systems to be adopted bydesigners and programmers in both academia and industry. Theseinclude the following topics: Agent Communication Technologies,Interoperability and Standards, Efficiency and Scalability Evalua-tion, Agent Infrastructure Benchmarks, Security, Privacy and

Identity Management in Multiagent Systems, Secure Infrastruc-tures and Tools for Multiagent Systems, Infrastructures and toolsthat support Social and Organizational Models, Infrastructuresand tools that support Trust and Reputation Models, Infrastruc-tures for agent-based Service-Oriented Systems, Industry imple-mentations of multiagent systems, etc.

Among the many different topics of interest, in this specialissue, ‘‘Infrastructures and Tools for Multiagent Systems forthe new generation of Distributed Systems’’, we focus on thefollowing:

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Social simulation. This is a research field that applies compu-tational methods to study issues in the social sciences.The challenges explored include problems in sociology, poli-tical science, economics, anthropology, geography, archeologyand linguistics (Takahashi et al., 2007). Two works in the socialsimulation area are presented in this special issue. Caballeroet al. (this issue) present a proposal for supporting cognitivebehavior of certain agents in wide social agent simulations.They propose using Jason to provide cognitive capabilities to areduced number of agents, running on a wide social simulationthat is supported by MASON. Marik and Pechoucek (2004)referto the knowledge necessary to give support to all these socialabstractions as social knowledge. They also point out that itplays an important role in increasing the efficiency in highlydecentralized multiagent systems. On the same topic, Burdaloet al. (this issue) present TRAMMAS, an abstract model of anevent-tracing system for multiagent systems. Unlike mosttraditional tracing systems, the model here is not only con-ceived as a helping tool for multiagent system developers oradministrators, but also as an additional indirect communica-tion mechanism that allows agents and other entities in thesystem to generate trace events, as well as to receive eventsgenerated by other entities. � Multiagent simulation. Developing tools for multiagent simu-

lations have always been an active area of research, withemphasis being placed on different aspects—architecture,scalability, efficiency, fault-tolerance, and effectiveness of thesystem. A number of frameworks have been developed such asNetlogo (Seth Tisue, 2004), JADE (Bellifemine et al., 1999),ZASE (Yamamoto et al., 2007), DMASF (Rao et al., 2007),MASON (Luke et al., 2005), and Repast (North et al., 2007).In this area, Sethia et al. (this issue) present a framework foragent simulation environment that is built on Hadoop cloud.Hadoop is a novel framework that runs applications thatinvolve thousands of nodes and petabytes of data. It allows adeveloper to focus on agent models and their optimizationwithout getting involved in fault-tolerance issues. Extensibilityof the hardware on which the framework is running is madeeasy by Hadoop. This is done by allowing the dynamic additionof new nodes and by allowing heterogeneity among theoperating systems on which the different nodes are running.Therefore, it provides a strong backbone for implementing alarge-scale, agent-based simulation framework.

� Security. Security-related studies in the multiagent systems

(MAS) research field have been increasing over the last fewyears, as have intelligent autonomous agents and MAS-basedapplications (Such et al., in press). An understanding of theactual risk is needed when using these sorts of applications,since an agent’s incorrect or inappropriate behavior may causeundesired effects such as money loss and data loss. For thistopic, Such et al. (this issue) propose formalized definitions ofpartial identities and their relationship to trust and reputation.Partial identities are a key concept for identifying entities.They also play a crucial role in trust and reputation, bymodeling part of the context where trust and reputation take

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place. In this sense, both trust and reputation are establishedthrough partial identities.

� Models of trust (Sierra and Debenham, 2006), reputation

(Sierra and Debenham, 2009), and argumentation (Amgoudand Prade, 2009; Alsinet et al., 2008) to improve negotiatingstrategies (Faratin et al., 1998; Kraus, 1997; Hindriks et al.,2008). Research progress in the development of these theore-tical models has made them very sophisticated and hasenabled software agents to interact with and help humans ina more efficient and believable way. For this topic, Fabregueset al. (this issue) present a testbed that provides an environ-ment where very expressive illocutions can be exchangedamong a small set of agents. Agents compete with the aim ofgetting more power; however, power is obtained by coopera-tion. To be able to increase your power, you have to convinceothers to help you. Thus, agents repeatedly negotiate toconvince others to accept a plan of action where both coop-erate and split the benefit. Being friendly, persuasive, loyal,and trustworthy are some of the skills that can be tested withthis testbed.

� Industry implementations of multiagent systems and wireless

sensor networks (WSNs) are currently emerging as one ofthe most innovative technologies, enabling and supportingthe next generation of ubiquitous and pervasive computingscenarios (Sohraby et al., 2007). WSNs are capable of support-ing a broad array of high-impact applications in severaldomains such as disaster/crime prevention, military, environ-ment, logistics, health care, and building/home automation.Programming WBSN applications is a complex task, it requiressuitable programming paradigms and frameworks that canhandle the specific characteristics of WBSN. Several kinds offrameworks and approaches have been proposed to date, andthe multiagent system approach is one of the more promising.For this topic, Aiello et al. (this issue) present an agent-oriented approach that relies on the basic features thatcharacterize domain-specific frameworks, as well as on theMAPS framework. This offers more programming effectivenesswhile providing the required efficiency. By using MAPS, aWBSN application has been structured as a set of agents thatare distributed on sensor nodes supported by a component-based agent execution engine that provides basic services suchas message transmission, agent creation, timer handling, easyaccess to the sensor node resources, and agent migration(if needed).

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