IAMOOC – Home

  • About IAMOOC

IAMOOC is a MOOC on Interval Analysis with application to parameter estimation and robot localization.

Interval analysis concerns the methods which  computes with intervals in place of real numbers. The applications are wide, including: Automatic, Optimization, Robotics, Chemistry. These techniques can deal with stability analysis, parameter estimation, validation of control systems, etc.
 
The registration is free.
The details of the programme are available here.
 
The participants who got satisfactory marks will receive a diploma corresponding this MOOC.

  • What is Interval Analysis?

Interval Computation is a numerical tool which allows us to solve nonlinear problems in a guaranteed way.  One of the pioneers of interval computations is Ramon E. Moore. He contributed largely to its development and dissemination. Nowadays, Interval Computations can be found in many fields: global optimization, set inversion, parameter estimation, localization of robots, etc.
 
Interval Computation offers a general numerical framework to easily get reliable results.
  • General Numerical Method 

Interval Computation can deal with a huge class of problems involving  equations or inequalities which can be non-smooth, non-convex, or with different kind of variables.
  • Easy

Interval tools are easy to understand. They only require basic knowledge on mathematics and computer sciences.
  • Guaranty – Reliability

The results provided by interval methods are guaranteed, which means that from correct assumptions, Interval Computations will provide correct conclusions. The results are guaranteed in any case. As a consequence, Interval Computations can be used to prove mathematical theorems. For instance, W. Tucker has proven the conjecture of Lorenz and Thomas Hales the conjecture of Kepler, both using Interval Computations.
  • Interval Computations Applied to Parameter Estimation

In this MOOC, we have chosen to illustrate interval methods in the context of parameter estimation,
for the following reasons:
  1.  estimation problems are generally nonlinear;
  2. guaranteed results are often required;
  3. estimation problems are frequently encountered in most of scientific fields.

 

  • Team

This course will be given by: