Pierrick Tranouez
Building upon Fast Multipole Methods to Detect and Model Organizations.
Wed, 10/07/2009 - 12:26 — SomNambulAuthors: Pierrick Tranouez, Antoine Dutot
Subjects: Artificial Intelligence
AbstractMany models in natural and social sciences are comprised of sets of
inter-acting entities whose intensity of interaction decreases with distance.
This often leads to structures of interest in these models composed of dense
packs of entities. Fast Multipole Methods are a family of methods developed to
help with the calculation of a number of computable models such as described
above. We propose a method that builds upon FMM to detect and model the dense
structures of these systems.A multiagent urban traffic simulation. Part II: dealing with the extraordinary.
Wed, 10/07/2009 - 12:26 — SomNambulAuthors: Pierrick Tranouez, Patrice Langlois, Eric Daudé
Subjects: Artificial Intelligence
AbstractIn Probabilistic Risk Management, risk is characterized by two quantities:
the magnitude (or severity) of the adverse consequences that can potentially
result from the given activity or action, and by the likelihood of occurrence
of the given adverse consequences. But a risk seldom exists in isolation: chain
of consequences must be examined, as the outcome of one risk can increase the
likelihood of other risks. Systemic theory must complement classic PRM. Indeed
these chains are composed of many different elements, all of which may have a
critical importance at many different levels.A multiagent urban traffic simulation Part I: dealing with the ordinary.
Tue, 09/08/2009 - 12:16 — SomNambulAuthors: Pierrick Tranouez, Patrice Langlois, Eric Daudé
Subjects: Artificial Intelligence
AbstractWe describe in this article a multiagent urban traffic simulation, as we
believe individual-based modeling is necessary to encompass the complex
influence the actions of an individual vehicle can have on the overall flow of
vehicles. We first describe how we build a graph description of the network
from purely geometric data, ESRI shapefiles. We then explain how we include
traffic related data to this graph.
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