Evolutionary Computation is an exciting research field with the power to assist researchers in the task of solving hard optimization problems (i.e., problems where the exploitable knowledge about the solution space is very hard and/or expensive to obtain). However, Evolutionary Algorithms are rarely used outside the circle of 'knowledgeable practitioners', and in that way have not achieved a status of 'useful tool' to assist ''general'' researchers. We think that part of the blame is the lack of practical implementations of research efforts reflecting a unifying common ground in the field.

In this talk I will present GUIDE, a software framework including a Graphical User Interface that allows the straightforward manipulation of evolutionary algorithms. From a high-level description provided by the user through the GUI, it generates the code that is needed to run an evolutionary algorithm in a specified existing library. GUIDE gives the user a straightforward understanding of EC ideas, while at the same time incorporating results from the research community. Particularly, it implements our latest research results on Adaptive Parameter Tuning, where we address the question: how to choose the 'optimal' operators to be applied to a specific problem? I will give an overview of the ideas we have applied to the solution of this question.

Finally, I will talk about 3 industrial case studies (two from the automobile industry and one from the software development industry) using GUIDE as one of the main tools in order to perform software testing on large, complex systems.

This 45-minute seminar will be given at 11:00 a.m. in room PLT-3775.