91,220 research outputs found

    Advances in infrastructures and tools for multiagent systems

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    In the last few years, information system technologies have focused on solving challenges in order to develop distributed applications. Distributed systems can be viewed as collections of service-provider and ser vice-consumer components interlinked by dynamically defined workflows (Luck and McBurney 2008).Alberola Oltra, JM.; Botti Navarro, VJ.; Such Aparicio, JM. (2014). Advances in infrastructures and tools for multiagent systems. Information Systems Frontiers. 16:163-167. doi:10.1007/s10796-014-9493-6S16316716Alberola, J. M., Búrdalo, L., Julián, V., Terrasa, A., & García-Fornes, A. (2014). An adaptive framework for monitoring agent organizations. Information Systems Frontiers, 16(2). doi: 10.1007/s10796-013-9478-x .Alfonso, B., Botti, V., Garrido, A., & Giret, A. (2014). A MAS-based infrastructure for negotiation and its application to a water-right market. Information Systems Frontiers, 16(2). doi: 10.1007/s10796-013-9443-8 .Andrighetto, G., Castelfranchi, C., Mayor, E., McBreen, J., López-Sánchez, M., & Parsons, S. (2013). (Social) norm dynamics. In G. Andrighetto, G. Governatori, P. Noriega, & L. W. van der Torre (Eds.), Normative multi-agent systems (pp. 135–170). Dagstuhl: Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik.Baarslag, T., Fujita, K., Gerding, E. H., Hindriks, K., Ito, T., Jennings, N. R., et al. (2013). Evaluating practical negotiating agents: results and analysis of the 2011 international competition. Artificial Intelligence, 198, 73–103.Boissier, O., Bordini, R. H., Hübner, J. F., Ricci, A., & Santi, A. (2013). Multi-agent oriented programming with JaCaMo. Science of Computer Programming, 78(6), 747–761.Campos, J., Esteva, M., López-Sánchez, M., Morales, J., & Salamó, M. (2011). Organisational adaptation of multi-agent systems in a peer-to-peer scenario. Computing, 91(2), 169–215.Carrera, A., Iglesias, C. A., & Garijo, M. (2014). Beast methodology: an agile testing methodology for multi-agent systems based on behaviour driven development. Information Systems Frontiers, 16(2). doi: 10.1007/s10796-013-9438-5 .Criado, N., Such, J. M., & Botti, V. (2014). Norm reasoning services. Information Systems Frontiers, 16(2). doi: 10.1007/s10796-013-9444-7 .Del Val, E., Rebollo, M., & Botti, V. (2014). Enhancing decentralized service discovery in open service-oriented multi-agent systems. Journal of Autonomous Agents and Multi-Agent Systems, 28(1), 1–30.Denti, E., Omicini, A., & Ricci, A. (2002). Coordination tools for MAS development and deployment. Applied Artificial Intelligence, 16(9–10), 721–752.Dignum, V., & Dignum, F. (2012). A logic of agent organizations. Logic Journal of IGPL, 20(1), 283–316.Ferber, J., & Gutknecht, O. (1998). A meta-model for the analysis and design of organizations in multi-agent systems. In Multi agent systems. Proceedings. International Conference on (pp. 128–135). IEEE.Fogués, R. L., Such, J. M., Espinosa, A., & Garcia-Fornes, A. (2014). BFF: a tool for eliciting tie strength and user communities in social networking services. Information Systems Frontiers, 16(2). doi: 10.1007/s10796-013-9453-6 .Garcia, E., Giret, A., & Botti, V. (2011). Evaluating software engineering techniques for developing complex systems with multiagent approaches. Information and Software Technology, 53(5), 494–506.Garcia-Fornes, A., Hübner, J., Omicini, A., Rodriguez-Aguilar, J., & Botti, V. (2011). Infrastructures and tools for multiagent systems for the new generation of distributed systems. Engineering Applications of Articial Intelligence, 24(7), 1095–1097.Jennings, N., Faratin, P., Lomuscio, A., Parsons, S., Sierra, C., & Wooldridge, M. (2001). Automated negotiation: prospects, methods and challenges. International Journal of Group Decision and Negotiation, 10(2), 199–215.Jung, Y., Kim, M., Masoumzadeh, A., & Joshi, J. B. (2012). A survey of security issue in multi-agent systems. Artificial Intelligence Review, 37(3), 239–260.Kota, R., Gibbins, N., & Jennings, N. R. (2012). Decentralized approaches for self-adaptation in agent organizations. ACM Transactions on Autonomous and Adaptive Systems (TAAS), 7(1), 1.Kraus, S. (1997). Negotiation and cooperation in multi-agent environments. Artificial Intelligence, 94(1), 79–97.Lin, Y. I., Chou, Y. W., Shiau, J. Y., & Chu, C. H. (2013). Multi-agent negotiation based on price schedules algorithm for distributed collaborative design. Journal of Intelligent Manufacturing, 24(3), 545–557.Luck, M., & McBurney, P. (2008). Computing as interaction: agent and agreement technologies.Luck, M., McBurney, P., Shehory, O., & Willmott, S. (2005). Agent technology: Computing as interaction (A roadmap for agent based computing). AgentLink.Ossowski, S., & Menezes, R. (2006). On coordination and its significance to distributed and multiagent systems. Concurrency and Computation: Practice and Experience, 18(4), 359–370.Ossowski, S., Sierra, C., & Botti. (2013). Agreement technologies: A computing perspective. In Agreement Technologies (pp. 3–16). Springer Netherlands.Pinyol, I., & Sabater-Mir, J. (2013). Computational trust and reputation models for open multi-agent systems: a review. Artificial Intelligence Review, 40(1), 1–25.Ricci, A., Piunti, M., & Viroli, M. (2011). Environment programming in multi-agent systems: an artifact-based perspective. Autonomous Agents and Multi-Agent Systems, 23(2), 158–192.Sierra, C., & Debenham, J. (2006). Trust and honour in information-based agency. In Proceedings of the 5th international conference on autonomous agents and multi agent systems, (p. 1225–1232). New York: ACM.Sierra, C., Botti, V., & Ossowski, S. (2011). Agreement computing. KI-Knstliche Intelligenz, 25(1), 57–61.Vasconcelos, W., García-Camino, A., Gaertner, D., Rodríguez-Aguilar, J. A., & Noriega, P. (2012). Distributed norm management for multi-agent systems. Expert Systems with Applications, 39(5), 5990–5999.Wooldridge, M. (2002). An introduction to multiagent systems. New York: Wiley.Wooldridge, M., & Jennings, N. R. (1995). Intelligent agents: theory and practice. Knowledge Engineering Review, 10(2), 115–152

    A Semantic-Agent Framework for PaaS Interoperability

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    Suchismita Hoare, Na Helian, and Nathan Baddoo, 'A Semantic-Agent Framework for PaaS Interoperability', in Proceedings of the The IEEE International Conference on Cloud and Big Data Computing, Toulouse, France, 18-21, July 2016. DOI: 10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0126 © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Cloud Platform as a Service (PaaS) is poised for a wider adoption by its relevant stakeholders, especially Cloud application developers. Despite this, the service model is still plagued with several adoption inhibitors, one of which is lack of interoperability between proprietary application infrastructure services of public PaaS solutions. Although there is some progress in addressing the general PaaS interoperability issue through various devised solutions focused primarily on API compatibility and platform-agnostic application design models, interoperability specific to differentiated services provided by the existing public PaaS providers and the resultant disparity owing to the offered services’ semantics has not been addressed effectively, yet. The literature indicates that this dimension of PaaS interoperability is awaiting evolution in the state-of-the-art. This paper proposes the initial system design of a PaaS interoperability (IntPaaS) framework to be developed through the integration of semantic and agent technologies to enable transparent interoperability between incompatible PaaS services. This will involve uniform description through semantic annotation of PaaS provider services utilizing the OWL-S ontology, creating a knowledgebase that enables software agents to automatically search for suitable services to support Cloud-based Greenfield application development. The rest of the paper discusses the identified research problem along with the proposed solution to address the issue.Submitted Versio

    OpenKnowledge at work: exploring centralized and decentralized information gathering in emergency contexts

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    Real-world experience teaches us that to manage emergencies, efficient crisis response coordination is crucial; ICT infrastructures are effective in supporting the people involved in such contexts, by supporting effective ways of interaction. They also should provide innovative means of communication and information management. At present, centralized architectures are mostly used for this purpose; however, alternative infrastructures based on the use of distributed information sources, are currently being explored, studied and analyzed. This paper aims at investigating the capability of a novel approach (developed within the European project OpenKnowledge1) to support centralized as well as decentralized architectures for information gathering. For this purpose we developed an agent-based e-Response simulation environment fully integrated with the OpenKnowledge infrastructure and through which existing emergency plans are modelled and simulated. Preliminary results show the OpenKnowledge capability of supporting the two afore-mentioned architectures and, under ideal assumptions, a comparable performance in both cases

    Deliverable JRA1.1: Evaluation of current network control and management planes for multi-domain network infrastructure

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    This deliverable includes a compilation and evaluation of available control and management architectures and protocols applicable to a multilayer infrastructure in a multi-domain Virtual Network environment.The scope of this deliverable is mainly focused on the virtualisation of the resources within a network and at processing nodes. The virtualization of the FEDERICA infrastructure allows the provisioning of its available resources to users by means of FEDERICA slices. A slice is seen by the user as a real physical network under his/her domain, however it maps to a logical partition (a virtual instance) of the physical FEDERICA resources. A slice is built to exhibit to the highest degree all the principles applicable to a physical network (isolation, reproducibility, manageability, ...). Currently, there are no standard definitions available for network virtualization or its associated architectures. Therefore, this deliverable proposes the Virtual Network layer architecture and evaluates a set of Management- and Control Planes that can be used for the partitioning and virtualization of the FEDERICA network resources. This evaluation has been performed taking into account an initial set of FEDERICA requirements; a possible extension of the selected tools will be evaluated in future deliverables. The studies described in this deliverable define the virtual architecture of the FEDERICA infrastructure. During this activity, the need has been recognised to establish a new set of basic definitions (taxonomy) for the building blocks that compose the so-called slice, i.e. the virtual network instantiation (which is virtual with regard to the abstracted view made of the building blocks of the FEDERICA infrastructure) and its architectural plane representation. These definitions will be established as a common nomenclature for the FEDERICA project. Other important aspects when defining a new architecture are the user requirements. It is crucial that the resulting architecture fits the demands that users may have. Since this deliverable has been produced at the same time as the contact process with users, made by the project activities related to the Use Case definitions, JRA1 has proposed a set of basic Use Cases to be considered as starting point for its internal studies. When researchers want to experiment with their developments, they need not only network resources on their slices, but also a slice of the processing resources. These processing slice resources are understood as virtual machine instances that users can use to make them behave as software routers or end nodes, on which to download the software protocols or applications they have produced and want to assess in a realistic environment. Hence, this deliverable also studies the APIs of several virtual machine management software products in order to identify which best suits FEDERICA’s needs.Postprint (published version

    Ensuring Cyber-Security in Smart Railway Surveillance with SHIELD

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    Modern railways feature increasingly complex embedded computing systems for surveillance, that are moving towards fully wireless smart-sensors. Those systems are aimed at monitoring system status from a physical-security viewpoint, in order to detect intrusions and other environmental anomalies. However, the same systems used for physical-security surveillance are vulnerable to cyber-security threats, since they feature distributed hardware and software architectures often interconnected by ‘open networks’, like wireless channels and the Internet. In this paper, we show how the integrated approach to Security, Privacy and Dependability (SPD) in embedded systems provided by the SHIELD framework (developed within the EU funded pSHIELD and nSHIELD research projects) can be applied to railway surveillance systems in order to measure and improve their SPD level. SHIELD implements a layered architecture (node, network, middleware and overlay) and orchestrates SPD mechanisms based on ontology models, appropriate metrics and composability. The results of prototypical application to a real-world demonstrator show the effectiveness of SHIELD and justify its practical applicability in industrial settings
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