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» Iterative Learning Control - Monotonicity and Optimization
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FLAIRS
2004
14 years 11 months ago
Developing Task Specific Sensing Strategies Using Reinforcement Learning
Robots that can adapt and perform multiple tasks promise to be a powerful tool with many applications. In order to achieve such robots, control systems have to be constructed that...
Srividhya Rajendran, Manfred Huber
ECAL
2005
Springer
15 years 3 months ago
A Dynamical Systems Approach to Learning: A Frequency-Adaptive Hopper Robot
We present an example of the dynamical systems approach to learning and adaptation. Our goal is to explore how both control and learning can be embedded into a single dynamical sys...
Jonas Buchli, Ludovic Righetti, Auke Jan Ijspeert
SAB
2010
Springer
147views Optimization» more  SAB 2010»
14 years 8 months ago
Fractal Gene Regulatory Networks for Robust Locomotion Control of Modular Robots
Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control...
Payam Zahadat, David Johan Christensen, Ulrik Pagh...
ICML
2009
IEEE
15 years 10 months ago
Robot trajectory optimization using approximate inference
The general stochastic optimal control (SOC) problem in robotics scenarios is often too complex to be solved exactly and in near real time. A classical approximate solution is to ...
Marc Toussaint
GECCO
2008
Springer
135views Optimization» more  GECCO 2008»
14 years 11 months ago
iBOA: the incremental bayesian optimization algorithm
This paper proposes the incremental Bayesian optimization algorithm (iBOA), which modifies standard BOA by removing the population of solutions and using incremental updates of t...
Martin Pelikan, Kumara Sastry, David E. Goldberg