874 search results - page 97 / 175 » Iterative Learning Control - Monotonicity and Optimization |
139
Voted
UAI
2008
15 years 4 months ago
2008
Continuous state spaces and stochastic, switching dynamics characterize a number of rich, realworld domains, such as robot navigation across varying terrain. We describe a reinfor...
118
Voted
CDC
2010
IEEE
14 years 9 months ago
2010
IEEE
Abstract-- The authors have extended deterministic portHamiltonian systems into stochastic dynamical systems which are described by stochastic differential equations written in the...
122
Voted
ATAL
2009
Springer
15 years 9 months ago
2009
Springer
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
261
Voted
ECAI
2010
Springer
15 years 3 months ago
2010
Springer
In the last decades enormous advances have been made possible for modelling complex (physical) systems by mathematical equations and computer algorithms. To deal with very long run...
123
Voted
ECML
2006
Springer
15 years 6 months ago
2006
Springer
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...