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RAS
2006
105views more  RAS 2006»
14 years 9 months ago
Reinforcement learning for quasi-passive dynamic walking of an unstable biped robot
A class of biped locomotion called Passive Dynamic Walking (PDW) has been recognized to be efficient in energy consumption and a key to understand human walking. Although PDW is s...
Kentarou Hitomi, Tomohiro Shibata, Yutaka Nakamura...

Publication
352views
15 years 5 months ago
Efficient methods for near-optimal sequential decision making under uncertainty
This chapter discusses decision making under uncertainty. More specifically, it offers an overview of efficient Bayesian and distribution-free algorithms for making near-optimal se...
Christos Dimitrakakis
73
Voted
WSC
2008
14 years 12 months ago
On step sizes, stochastic shortest paths, and survival probabilities in Reinforcement Learning
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
Abhijit Gosavi
NECO
2010
97views more  NECO 2010»
14 years 8 months ago
Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning
Most conventional Policy Gradient Reinforcement Learning (PGRL) algorithms neglect (or do not explicitly make use of) a term in the average reward gradient with respect to the pol...
Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto...
ICRA
2009
IEEE
143views Robotics» more  ICRA 2009»
15 years 4 months ago
Least absolute policy iteration for robust value function approximation
Abstract— Least-squares policy iteration is a useful reinforcement learning method in robotics due to its computational efficiency. However, it tends to be sensitive to outliers...
Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashim...