Complexity, Networks, Geosimulations

UNIL | Université de Lausanne

Citadyne - Conferences 2010: The goal of this conference is to present the most exciting complex-systems research taking place in the social, economical, biological, and physical arenas to the Geo, Environment and Social sciences communities.

Episodes

  1. 06/11/2010 · VIDEO

    The complexity of structure, strategy and decision making

    Prof. Peter ALLEN, Cranfield University, United Kingdom. Many spatial models are really ‘fitted descriptions’ of spatial changes that have occurred. In order to have a deeper and possibly more long term understanding of what is going on, or may happen, it is necessary to represent the behaviours, interactions and circumstances of the different agents within the system and to explore not only how their locations and size may change, but also how their activities, technologies, needs and requirements may change over time. This presentation looks at how complex systems models attempt to do this, and how this led to ‘multi-agent’ models several decades ago. The different types of agent are distributed spatially across the transport and communication networks of a region, both responding to, and shaping these over time. The models then show different possible patterns of spatial organization that can emerge, and allow us to see how stable different possible trajectories might be. Such models can form the basis of a ‘learning’ community, city or region where modellers, institutions, organizations and firms try to experiment and learn together about the possibilities that are open to them. This underlines the problems of finding successful levels of evaluation for decisions and policies and making operational models that reflect the spatial realities of subsidiarity for different phenomena and issues.

    50 min
  2. 06/10/2010 · VIDEO

    Geo-simulations of urban phenomena

    Prof. Itzhak BENENSON, Geography, University of Tel-Aviv, Israel. Geosimulation treats the city as a creature, the complexity of which is above the complexity of physical and chemical systems, but below the complexity of a human self. It thus assumes that there is no need to directly account for real complexity of urban inanimate and animate objects when formalizing urban phenomena. Instead, we could succeed with the agents, which exhibit simple human-like activities that drive the city and its dynamics. The decade of accumulating of the high-resolution GIS, Remote Sensing, population and movement data resulted in cardinal change in the data availability. New sets of data feed Geosimulation models with the adequate behavioral rules and likelihood estimates of parameters, thus bringing us closer to the ultimate goal of Geosimulation - spatially explicit dynamic modeling of urban phenomena. However, these rules necessarily reflect the bounded rationality, i.e., essential uncertainty, of the human behavior. Based on several examples related to the fields of urban and regional planning, land-use dynamics, residential dynamics and urban traffic, I analyze the reasons why some of the Geosimulation models succeed, while some of them do not. I further suggest employing Geosimulation as a tool for understanding inherent uncertainty of urban dynamics and, in this way, for adequate estimating of our ability to predict complex urban phenomena.

    1h 10m
  3. 06/10/2010 · VIDEO

    Computational physics for the study of complex networks

    Prof. Roger GUIMERA & Prof. Marta SALES, Biochimics, Universitat Rovira i Virgili, Tarragona, Spain. Cells, the brain, ecosystems and economies are complex systems. In complex systems, individual components interact with each other, usually in nonlinear ways, giving rise to complex networks of interactions that are neither totally regular nor totally random. Partly because of the interactions themselves and partly because of the interaction topology, complex systems cannot be properly understood by just analyzing their constituent parts. For example, one cannot properly understand consciousness by studying isolated neurons, or economic crises by studying isolated individuals. The reason why complex networks of interactions are non-trivial is that any bias, however small, in the way components establish connections gives rise to structural correlations. This makes understanding complex systems challenging but, at the same time, it means that each network contains, hidden within its structure, important clues about how the system operates and evolves. Recent technological developments have made it possible to gather unprecedented amounts of data on a variety of complex systems from social to biological. However, our knowledge on these systems has not increased proportionally due to the lack of tools to extract information from large pools of data and to assess data reliability. In this talk we will discuss recent developments on complex networks theory that tackle the aforementioned challenges and what are the implications for systems biology and social problems.

    55 min

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Citadyne - Conferences 2010: The goal of this conference is to present the most exciting complex-systems research taking place in the social, economical, biological, and physical arenas to the Geo, Environment and Social sciences communities.

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