Complex Networks


Many of the systems that can be found in our environment can be modeled as complex adaptive systems that consist of a dynamic network of agents (which may represent individuals, businesses, services, resources) that perform a set of activities in parallel and react to what other agents are doing. Multiagent systems are considered a suitable tool for the study of complex adaptive systems and specially those distributed and dynamic. A simple way of analyzing these systems is to consider them as a network, that is, a discrete set of entities (nodes) and a set of connections (links) between these entities.

The area of complex networks focuses on the study of networks and is based on previous work in the area of graph theory. However, the area of complex networks differs from the more traditional view of graph theory in the following aspects:

  1. it focuses on the study of the properties of networks not only from a theoretical point of view but also from an experimental point of view. The analyzed networks emerge in a natural way in the real world, evolving in an unsupervised and decentralized way (eg World Wide Web, transportation networks, power grids, financial networks, scientific collaborations.)
  2. networks are considered not only as the topology of systems, but also as a framework where entities that are part of this topology interact;
  3. the area of complex networks takes into account the evolution of the network according to a set of dynamic rules. Networks are considered as the product of dynamic processes that occur over time that add/remove nodes or links.

In our research group, we are working on different lines where there is an integration of complex systems with intelligent systems:

  1. Analysis of the influence of different types of network structures in distributed resource management in agent societies.
  2. Self-adaptation mechanisms in networks to improve network navigation.
  3. Influence of the network structure in the emerge of cooperation in agents societies
  4. Development of unsupervised agreements between intelligent autonomous entities using consensus processes in networks.
  5. Analysis of the evolution of structural properties in social networks

The research projects associated to this research line are the following:

Current projects:
  • iHAS: Human-Agent societies : Design, Formation and Coordination
  • Social and Economic computing.
Past projects:
  • Agreement Technologies
  • Consensus Networks for the Non-Supervised Elaboration of Agreements among Autonomous Intelligent Entities
  • Adaptive Virtual Organizations: Architecture and development methods