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MASINGER group
Dr. Ferrante Neri
Department of Mathematical Information Technology,
University of Jyväskylä, Finland
10th May 2010
MASINGER group
Memetic
Algorithms, Swarm
Intelligence,
Networks, Genetic
and Evolutionary
Robotics
Group Members 1/2
Dr. Ferrante Neri
Dr. Ernesto Mininno
Dr. Ville Tirronen
02/17/10
Group Members 2/2
Ph. Lic Matthieu Weber
Mr. Giovanni Iacca
02/17/10
Structure of the Group
• Horizontal and Non-hierarchical
• Everybody is fundamental within its role
JUST LIKE A FOOTBALL TEAM !!
02/17/10
Research Topics at the first glance
Computational Intelligence Optimization
When the problem cannot be solved by means
of an exact method due to the lack of
differentiability or even analytic expression
an alternative way must be found
02/17/10
Research Topics in details 1/2
Methodologies:
– Memetic Computing
Encoding of culture into optimization
algorithms, e.g. hybrid approaches,
integration of knowledge
– Differential Evolution
Specific Oprimization Algorithm for continuous
problems
Research Topics in details 2/2
Applications:
– Evolutionary Optimization in the Presence
of Uncertainties
– Large Scale and Computationally
Expensive Optimization Problems
02/17/10
Current Research Lines
Distributed Memetic/Evolutionary
Algorithms
Compact Memetic/Evolutionary
Algorithms
Distributed Algorithms
•
If a population is properly structured,
with no additional overhead, the
performance might be significantly
improved and thus highly dimensional
problems (1000 D) can be handled.
Compact Algorithms
– belong to the class of Estimation Distribution
Algorithms
– do not use a population of individuals
– make use of a statistic representation of the
population
This approach is necessary to solve complex
optimization problems despite the absence of a
full performance computer
Graphical Convergence
Representation
Compact Algorithms in
Real-World
Automotive
Aerospace
Medical engineering
Robotics
Manufacturing
Performances depend on the control system tuning.
Application Example
•A cartesian robot controller for pick&place
•Compact algorithm to optimize the
nonlinear controller (NN)
•The system has been optimized in order
to reject the unpredictable payload variatio
•No external computer has been used
•Details on IEEE Computational Intelligenc
Magazine, May 2010
Questions?