<%@LANGUAGE="JAVASCRIPT" CODEPAGE="1252"%> About Fabio Boschetti
Fabio Boschetti,
Research Scientist,
CSIRO CMAR, Australia
Publications
Complex System Science
Ecological Modelling
Can we learn how systems work?
Agent Based, Economic Modelling & Game Theory
Emergence
Modelling the non-separability of a very complex world (ECCS'10)
Optimisation
Visualisation of scientific data
Geophysics
CV
Contacts
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Optimisation

Mathematical knowledge mostly expresses itself via 'forward modeling', that is the ability to describe the result of a process acting under certain initial conditions (cause -> effect framework). However, scientific quest usually strives for the opposite, that is, to define the causes which lead to specific effects (cause <- effects). Roughly, this is what inverse theory is about. For only very few problems a direct solution to the effect->cause problem can be found, so inversion is mostly about more or less cleverly designed heuristics.

I have applied inversion to very different mathematical problems with the purpose of building a tool for expert users as well as for users with little mathematical background. The inversion strategy is based mainly on the four components described below; depending on the expertise, the various components can be used differently:

 

Optimization routines

Interactive Inversion

This is a surprising powerful technique in which the traditional numerical cost function is replaced by a subjective user evaluation

Parameter space visualisation

We consider this an integral part of an optimisation process. See here.

Applications