85,551 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 normative approach to multi-agent systems for intelligent buildings

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    Building Management Systems (BMS) are widely adopted in modern buildings around the world in order to provide high-quality building services, and reduce the running cost of the building. However, most BMS are functionality-oriented and do not consider user personalization. The aim of this research is to capture and represent building management rules using organizational semiotics methods. We implement Semantic Analysis, which determines semantic units in building management and their relationship patterns of behaviour, and Norm Analysis, which extracts and specifies the norms that establish how and when these management actions occur. Finally, we propose a multi-agent framework for norm based building management. This framework contributes to the design domain of intelligent building management system by defining a set of behaviour patterns, and the norms that govern the real-time behaviour in a building

    On the linear convergence of distributed Nash equilibrium seeking for multi-cluster games under partial-decision information

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    This paper considers the distributed strategy design for Nash equilibrium (NE) seeking in multi-cluster games under a partial-decision information scenario. In the considered game, there are multiple clusters and each cluster consists of a group of agents. A cluster is viewed as a virtual noncooperative player that aims to minimize its local payoff function and the agents in a cluster are the actual players that cooperate within the cluster to optimize the payoff function of the cluster through communication via a connected graph. In our setting, agents have only partial-decision information, that is, they only know local information and cannot have full access to opponents' decisions. To solve the NE seeking problem of this formulated game, a discrete-time distributed algorithm, called distributed gradient tracking algorithm (DGT), is devised based on the inter- and intra-communication of clusters. In the designed algorithm, each agent is equipped with strategy variables including its own strategy and estimates of other clusters' strategies. With the help of a weighted Fronbenius norm and a weighted Euclidean norm, theoretical analysis is presented to rigorously show the linear convergence of the algorithm. Finally, a numerical example is given to illustrate the proposed algorithm

    Towards time-varying proximal dynamics in Multi-Agent Network Games

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    Distributed decision making in multi-agent networks has recently attracted significant research attention thanks to its wide applicability, e.g. in the management and optimization of computer networks, power systems, robotic teams, sensor networks and consumer markets. Distributed decision-making problems can be modeled as inter-dependent optimization problems, i.e., multi-agent game-equilibrium seeking problems, where noncooperative agents seek an equilibrium by communicating over a network. To achieve a network equilibrium, the agents may decide to update their decision variables via proximal dynamics, driven by the decision variables of the neighboring agents. In this paper, we provide an operator-theoretic characterization of convergence with a time-invariant communication network. For the time-varying case, we consider adjacency matrices that may switch subject to a dwell time. We illustrate our investigations using a distributed robotic exploration example.Comment: 6 pages, 3 figure

    Norm Monitoring under Partial Action Observability

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    In the context of using norms for controlling multi-agent systems, a vitally important question that has not yet been addressed in the literature is the development of mechanisms for monitoring norm compliance under partial action observability. This paper proposes the reconstruction of unobserved actions to tackle this problem. In particular, we formalise the problem of reconstructing unobserved actions, and propose an information model and algorithms for monitoring norms under partial action observability using two different processes for reconstructing unobserved actions. Our evaluation shows that reconstructing unobserved actions increases significantly the number of norm violations and fulfilments detected.Comment: Accepted at the IEEE Transaction on Cybernetic
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