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?