A very interesting, long course in Italy, very relevant to ECCO's
recent research, e.g. by Marko, Carlos, Dirk and Andreas.
(unfortunately, registration seems closed already). I suppose Carlos
knows these people...
-------EU
EXYSTENCE
Thematic
Institute:
Information and Material Flows
in Complex Networks, June 15 to July 15
http://www.trafficforum.org/ti
Some excerpts of the program:
Information Flows in Social
Networks
Life without information is not life. From the generic blueprint in our DNA to the world wide Internet, information and its dynamic counterpart communication define our civilization. However, we live under the limited information horizon, in the sense that information is often imperfect and communication is always finite. In recent years, it has become clear that the modeling of some phenomena, particularly ecological and social phenomena, requires agents whose behavior is not simply dictated by local, state-determined interaction. In a society empowered by language and hyperlinked by information channels, which in turn impacts planetary ecology, agents have access and rely on accumulated knowledge which escapes local constraints (via communication) and is stored in media beyond the agent itself and its state. Indeed, many if not most researchers in Artificial Intelligence (AI), Cognitive Science and Psychology, have come to pursue the idea that intelligence is not solely an autonomous characteristic of agents, but heavily depends on social, linguistic, and organizational knowledge which exists beyond individual agents. Such agents are often known as situated or semiotic agents. It has also been shown that agent simulations which rely on shared social knowledge can model social choice more effectively. We are, therefore, interested in studying how agents trade and employ knowledge in their decision making. Moreover, we would like to explore the structure of social networks arising out of agents who exchange knowledge, as well as the dynamics of trends observed in such multi-agent systems. For example, one may use existing networks of documents (e.g. the WWW and databases with scientific publications), to discover the dynamics of knowledge in user communities. Recently, methods have been developed to predict trends and identify latent associations between agents, documents, or key terms. Latent associations are associations (say between agents) that have not occurred, but which are strongly implied by indirect network connections, and thus have a high chance of occurring in the future. This methodology has, for example, been used in a recommendation system for the MyLibray Portal at Los Alamos and to study terrorist networks in Homeland Defense projects.
Life without information is not life. From the generic blueprint in our DNA to the world wide Internet, information and its dynamic counterpart communication define our civilization. However, we live under the limited information horizon, in the sense that information is often imperfect and communication is always finite. In recent years, it has become clear that the modeling of some phenomena, particularly ecological and social phenomena, requires agents whose behavior is not simply dictated by local, state-determined interaction. In a society empowered by language and hyperlinked by information channels, which in turn impacts planetary ecology, agents have access and rely on accumulated knowledge which escapes local constraints (via communication) and is stored in media beyond the agent itself and its state. Indeed, many if not most researchers in Artificial Intelligence (AI), Cognitive Science and Psychology, have come to pursue the idea that intelligence is not solely an autonomous characteristic of agents, but heavily depends on social, linguistic, and organizational knowledge which exists beyond individual agents. Such agents are often known as situated or semiotic agents. It has also been shown that agent simulations which rely on shared social knowledge can model social choice more effectively. We are, therefore, interested in studying how agents trade and employ knowledge in their decision making. Moreover, we would like to explore the structure of social networks arising out of agents who exchange knowledge, as well as the dynamics of trends observed in such multi-agent systems. For example, one may use existing networks of documents (e.g. the WWW and databases with scientific publications), to discover the dynamics of knowledge in user communities. Recently, methods have been developed to predict trends and identify latent associations between agents, documents, or key terms. Latent associations are associations (say between agents) that have not occurred, but which are strongly implied by indirect network connections, and thus have a high chance of occurring in the future. This methodology has, for example, been used in a recommendation system for the MyLibray Portal at Los Alamos and to study terrorist networks in Homeland Defense projects.
Traffic Control and
Production Scheduling
Traffic flow in urban road networks can be essentially treated as a queuing or supply network. Street segments play the role of buffers, and cars correspond to products. Instead of being modified by machines, they are served by traffic lights, and travel times correspond to cycle times. In many respects, traffic networks can therefore serve as paradigm of production processes. Conflicting goals, for example, are reflected by conflicting vehicle flows at intersections. To resolve them, one needs to find suitable priority rules. Algorithms for traffic optimization can have interesting implications for production scheduling and vice versa. Even the organization of social systems can profit from such insights, as they share many common features with production systems and supply networks. Another interesting subject is traffic optimization based on inter-vehicle communication. Information exchange of vehicles allows not only to determine the local traffic situation in a distributed way. It also facilitates to warn other vehicles of forthcoming traffic jams and to induce appropriate adaptations (e.g. speed adjustments or leaving of congested road sections). In this way, the safety, comfort, reliability and capacity of the system can be increased. In some respect, traffic assistence systems of the future will have features such as attention, learning capabilities, and awareness. Moreover, the method of information processing is of particular interest in itself: Inter-vehicle communication is based on ad-hoc networks with limited information transmission capacity. It is, therefore, highly essential to separate relevant from irrelevant (e.g. old) information. Moreover, the network of equipped vehicles is extremely sparse, and information unreliable and delayed. For this reason, measurements need to be complemented by suitable models.
Traffic flow in urban road networks can be essentially treated as a queuing or supply network. Street segments play the role of buffers, and cars correspond to products. Instead of being modified by machines, they are served by traffic lights, and travel times correspond to cycle times. In many respects, traffic networks can therefore serve as paradigm of production processes. Conflicting goals, for example, are reflected by conflicting vehicle flows at intersections. To resolve them, one needs to find suitable priority rules. Algorithms for traffic optimization can have interesting implications for production scheduling and vice versa. Even the organization of social systems can profit from such insights, as they share many common features with production systems and supply networks. Another interesting subject is traffic optimization based on inter-vehicle communication. Information exchange of vehicles allows not only to determine the local traffic situation in a distributed way. It also facilitates to warn other vehicles of forthcoming traffic jams and to induce appropriate adaptations (e.g. speed adjustments or leaving of congested road sections). In this way, the safety, comfort, reliability and capacity of the system can be increased. In some respect, traffic assistence systems of the future will have features such as attention, learning capabilities, and awareness. Moreover, the method of information processing is of particular interest in itself: Inter-vehicle communication is based on ad-hoc networks with limited information transmission capacity. It is, therefore, highly essential to separate relevant from irrelevant (e.g. old) information. Moreover, the network of equipped vehicles is extremely sparse, and information unreliable and delayed. For this reason, measurements need to be complemented by suitable models.
EU EXYSTENCE
Program
From June 24 to June 30, we will have an international workshop on INFORMATION AND MATERIAL FLOWS IN COMPLEX NETWORKS at Goldrain Castle with many interesting talks. It will be part of the four-week Thematic Institute which will try to push this challenging and promising field forward.
Participants and tentative titles of their talks:
to be announced
"Bankruptcy cascade in Production Networks"
"Theoretical Analysis of Local Information Transmission in Competitive Populations"
"Probabilistic study of complex networks"
"Modelling and analysis of autonomous shop floor logistics"
to be announced
to be announced
"Engineering of Functional Networks"
"Entrainment of complex oscillator networks by a pacemaker: its dynamics and optimization"
"Adaptive Traffic Light Control and Traffic Assignment in Urban Road Networks"
"Towards an operationalization of complexity measures for logistics systems"
"Modeling, Validation and Control of Manufacturing Systems"
"Food-web representation of agent interaction in a spatial IPD"
to be announced
"Agent-Based Modelling Methodologies"
"The Role of Border Collision Bifurcations in Manufacturing Systems, or: On the Dynamics of Logistic"
to be announced
"The growth and form of self-organized planar networks in animal and human societies"
"Integrated traffic simulation of assistance systems including vehicle-vehicle communication"
to be announced
--
Francis Heylighen
Evolution, Complexity and Cognition group
Free University of Brussels
http://pespmc1.vub.ac.be/HEYL.html
Francis Heylighen
Evolution, Complexity and Cognition group
Free University of Brussels
http://pespmc1.vub.ac.be/HEYL.html
