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 ABS2
Agent Based
Spatial Simulation

International Workshop
    24-25 November 2008    
ISC-PIF, Paris, France

 

New : ABS2 Presentations

 

Final Program: ( Program-ABS2.pdf)

Final Program With Abstracts: ( FullProgram-ABS2.pdf)

 

How to get there


Organisers

Arnaud Banos, Image et Ville (UMR 7011 CNRS/ULP)
Frederic Amblard, IRIT (UMR 5055 CNRS/Université de Toulouse)
Christophe Lang, LIFC (EA 4157, Université de Franche-Comté)

Scientific Committee

Mike Batty (CASA-UCL, London)
Nigel Gilbert (University of Surrey, Guildford)
Tim Kohler (Washington State University)
Lael Parrott (Complex Systems Laboratory, University of Montreal)
Denise Pumain (Géographie-Cités, Paris)
Frank Schweitzer (ETH, Zurich)

Keynote speakers

Volker Grimm, UFZ Centre for Environmental Research Leipzig-Halle, Germany: Individual-based models in ecology
Philippe Mathieu, LIFL, University of Lille, France: New approaches for Situated Agent Systems


Topic of the Workshop
[Download the initial call: (Call-ABS2.pdf)]

Agent Based Models are privileged tools in many different disciplines, when it comes to the exploration of complex systems. Indeed, they allow to model processes from the bottom-up and to simulate the behaviour of a large variety of phenomena, ranging from physical, biological, social, cultural and cognitive domains.

In some specific communities, including geography, planning, architecture, archaeology, sociology, spatial economics, computer sciences, ecology, to name but a few, some specific models have also been imagined, designed and tested, which allow exploring complex spatial systems.

In that perspective, spatially explicit agent based models are the focus of this international workshop, organised as a joint event between the Paris-Île de France Complex Systems Institute (ISC-PIF) and the European Network “Spatial Simulation for the Social Sciences” (S4), and especially its SIMBAAD working group: “Simulation Based of Agents to Aid Decision”.

Contributions dealing with (but not limited to) the following fields of spatially explicit ABM are encouraged:

•    Formalising spatial structures and processes in agent based models
•    Coupling environmental and social processes
•    Formalising incomplete information and/or bounded rationality in space
•    Modelling perception of space by agents
•    Identifying and comparing emerging spatial patterns

•    Feeding and calibration of agent models with heterogeneous and multi-sources data
•    Verification and validation of individual and global behaviour
•    Real-time coupling between empirical data and model
•    Parallelisation and grid computing for large spatial models, including distributed problems: distributed clocks, synchronisation, load-sharing.

•    Re-interpreting classic macroscopic models using an ABM approach
•    Spatial agent based models for exploration, optimisation, decision support

 

 

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