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» Iterative Learning Control - Monotonicity and Optimization
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CEC
2007
IEEE
15 years 4 months ago
Parallel learning in heterogeneous multi-robot swarms
Abstract— Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using unsupervised learning techniques w...
Jim Pugh, Alcherio Martinoli
AUTOMATICA
2004
70views more  AUTOMATICA 2004»
14 years 9 months ago
Output feedback control of discrete linear repetitive processes
Repetitive processes are a distinct class of 2D systems (i.e. information propagation in two independent directions) of both systems theoretic and applications interest. They cann...
Bartlomiej Sulikowski, Krzysztof Galkowski, Eric R...
IJON
2002
154views more  IJON 2002»
14 years 9 months ago
Nonlinear model predictive control of a cutting process
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...
Primoz Potocnik, Igor Grabec
KDD
2001
ACM
166views Data Mining» more  KDD 2001»
15 years 10 months ago
Generalized clustering, supervised learning, and data assignment
Clustering algorithms have become increasingly important in handling and analyzing data. Considerable work has been done in devising effective but increasingly specific clustering...
Annaka Kalton, Pat Langley, Kiri Wagstaff, Jungsoo...
ICML
2006
IEEE
15 years 10 months ago
A new approach to data driven clustering
We consider the problem of clustering in its most basic form where only a local metric on the data space is given. No parametric statistical model is assumed, and the number of cl...
Arik Azran, Zoubin Ghahramani