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» Policy Gradient Methods for Robotics
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NIPS
2001
13 years 9 months ago
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...
ICRA
2009
IEEE
255views Robotics» more  ICRA 2009»
14 years 2 months ago
Combining color-based invariant gradient detector with HoG descriptors for robust image detection in scenes under cast shadows
— In this work we present a robust detection method in outdoor scenes under cast shadows using color based invariant gradients in combination with HoG local features. The method ...
Michael Villamizar, Jorge Scandaliaris, Alberto Sa...
ICRA
2009
IEEE
125views Robotics» more  ICRA 2009»
14 years 2 months ago
A novel method for learning policies from constrained motion
— Many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the environment. Constraints are usually unobservable and frequently...
Matthew Howard, Stefan Klanke, Michael Gienger, Ch...
MATES
2004
Springer
14 years 1 months ago
Policies for Cloned Teleo-reactive Robots
This paper presents a new method for predicting the values of policies for cloned multiple teleo-reactive robots operating in the context of exogenous events. A teleo-reactive robo...
Krysia Broda, Christopher J. Hogger
JMLR
2006
143views more  JMLR 2006»
13 years 7 months ago
Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation
We study a sequential variance reduction technique for Monte Carlo estimation of functionals in Markov Chains. The method is based on designing sequential control variates using s...
Rémi Munos