Complex Networks

Overview
  • Analysis of the influence of different types of network structures in distributed resource management in agent societies.

    Service-oriented multi-agent systems are dynamic systems populated by heterogeneous agents. These agents model their functionality as services in order to allow heterogeneous agents or other entities to interact with each other in a standardized way. Furthermore, due to the large-scale and adaptative needs of the system, traditional directory facilitators or middle-agents are not suitable for the management of agent services. We are working on the creation of efficient decentralized and self-organized structures that facilitate the service discovery. Specifically, we have proposed a structure based on a self-organizing feature called homophily. This feature makes that agents have a greater probability of establishing links with similar agents than with dissimilar ones. This similarity is based on two social dimensions: the set of services that an agent provides and the organizational roles that it plays. Moreover, we have proposed an algorithm for service discovery that it is carried out taking into account the local information that is related to the homophily between agents.

  • Self-adaptation mechanisms in networks to improve network navigation.

    Service discovery is a challenging task in large-scale, complex, and highly-dynamic systems when changes in the environment occur (i.e., distribution of service demand, agents that leave and enter the system) and there is no central repository responsible for the management of resources and the maintenance of the system structure. Therefore, each agent should be able to locate another agent that provides the required service and to update its structural links to obtain more useful relations. The success of the service discovery process relies on the collaboration of other agents in the system and the self-organization of the structural relations between agents. In systems where the environmental conditions or requirements change and nodes only have local knowledge, the inclusion of self-organization mechanisms offers advantages such as increased scalability and robustness and a reduced need for communication. We are working on a decentralized service discovery system that integrates mechanisms to facilitate the self-organization of the structural relations established among agents and the system population in order to adapt the system structure to the service demand.

  • Influence of the structure in the emerge of cooperation in agents societies

    In distributed environments where entities only have a partial view of the system, cooperation plays a key issue. In the case of decentralized discovery of resources in open Service-Oriented Multi-Agent Systems, agents only know about the resources they provide and their direct neighbors. Therefore, they need the cooperation of their neighbors in order to locate the required resources. However, cooperation is not always present in open and distributed systems. Non-cooperative agents pursuing their own goals could refuse to forward queries from other agents to avoid the cost of this action; therefore, the efficiency of the decentralized resource discovery could be seriously damaged. We are working on modeling cooperation scenarios using game theory approaches and analyzing the influence of network configuration in the emergence of cooperation.

  • Development Unsupervised agreements between intelligent autonomous entities using consensus processes in networks.

    In recent years, there is an interest in the problem of decentralized consensus. Specially, the researchers focus on getting algorithms that are able to reach global agreements on agent networks through local interactions only, i.e. without knowledge of other agents that are part of the network and working only with the information available from immediate neighbors.

    We are working on negotiation mechanisms to build agreement spaces where a group of intelligent entities can negotiate the dimensions related to the agreement (its variables) and then reach an agreement or enclose the space of possible solutions. The technique used for the establishment of agreements is based on a consensus process in networks.

  • Analysis of the evolution of the structural properties in social networks

    The number of people using on-line social networks as a new way of communication is increasing. The messages that a user writes in these networks and his/her interactions with other users leave a digital trace that is recorded. Thanks to this fact and the use of network theory, the analysis of messages, user interactions, and the complex structures that emerge is greatly facilitated. In addition, information generated in on-line social networks is labeled temporarily, which makes possible to go a step further analyzing the dynamics of the interaction patterns. We are working on the analysis of the evolution of user interactions that take place in television, socio- political, conferences, and keynotes events in Twitter. Interactions have been modeled as networks temporarily annotated. We study changes in the structural properties at network level and node level as well as patterns of network evolution and common and different structural features between some events.