Probabilistic Control and Applications to Gene Regulatory Networks
Miguel José Simões Barão,
R – INESC-ID Lisboa –
Abstract:
Probabilistic control aims to find a probabilistic decision rule in order to
control a stochastic dynamic system. In this formulation, both the system
model and decision rules are described by conditional probability functions
that are iterated together in a closed loop.
This kind of formulation fits well in problems where a large number of agents
act on the same system simultaneously, one possible application being gene
regulatory networks.
This talk addresses the formulation of the probabilistic control problem, the
optimization of probability functions, and an illustration of its application
to gene regulatory network.
It is shown that despite the original problem is a high dimensional one, its
solution can be computed in a very efficient way.
Date: 2008-Nov-13 Time: 15:00:00 Room: 336
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Keynote speakers:
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Russell Schwartz, Carnegie Mellon University (class and hands-on)
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