TALK ANNOUNCEMENT
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Priberam Machine Learning Lunch Seminar
Speaker: Stefano Ruberto (INESC-ID)
Venue: IST Alameda, Sala PA2 (Edifício de Pós-Graduação)
Date: Tuesday, June 4th, 2013
Time: 13:00
Lunch will be provided
Title: "Semantic Approach in Genetic Programming"
Abstract:
Evolutionary algorithms are stochastic optimization techniques based on
the principles of natural evolution, and Genetic Programming (GP)
belongs to this family. In recent years the study of GP systems has been
extended to phenotypic aspects, while previously it was mainly focused
on genotypic and syntactic aspects. Phenotypic properties, or semantics,
is used with the aim of optimizing the ability of GP algorithms to
explore the solution space in an effective way, increasing the
probability of finding an optimal solution and escaping local optima.
Currently, semantic GP is strictly related to the evaluation of
individual behavior in the candidate population: this kind of evaluation
is mainly obtained through the fitness function itself. This work
introduces a new way of measuring semantic similarity between
individuals that is more independent from the fitness itself, allowing a
fair comparison even when the fitness values involved are far away from
each other. This new measure enables a new series of techniques to be
used to tackle the open problems in GP, like bloat and overfitting, and
also targeting the phenotype variety preservation, thereby enhancing
performance. Preliminary results will be provided. A new theoretical GP
algorithm based on this new semantic measure is also introduced, showing
the potential advantages. Very early results coming from a first naive
implementation show interesting insight on this potential, when compared
with other cutting edge algorithms.
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Bio: Stefano Ruberto was born in Firenze, Italia (1974). He earned his
bachelor degree with honours from Università dell'Insubria in 2005,
while working as an IT consultant in the fashion industry where, his
interests in fractal and automatic image composition were greatly
appreciated.
Stefano's interest in Artificial Intelligence and modelling were
adequately nourished while he was working at KFT, a multi-national
company in security and telecommunication. There, he could not only
develop real world physics model of radio transmission for telephone
triangulation, but also develop models for interpreting data from low
cost MEMES accelerometers, gyroscopeand compass, that are applied to
innovative automotive. Models aimed at vehicular traffic prediction were
also developed. Finally, Stefano graduated with honours from University
of Milano Bicocca in 2013. Currently he is a research fellow at
INESC-ID, working on Genetic Programming with special focus on new
semantic approaches for the novel field of Semantic GP.
