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ECML
2007
Springer
13 years 12 months ago
Policy Gradient Critics
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
Daan Wierstra, Jürgen Schmidhuber
ICRA
2009
IEEE
132views Robotics» more  ICRA 2009»
14 years 12 days ago
Smoothed Sarsa: Reinforcement learning for robot delivery tasks
— Our goal in this work is to make high level decisions for mobile robots. In particular, given a queue of prioritized object delivery tasks, we wish to find a sequence of actio...
Deepak Ramachandran, Rakesh Gupta
IJCAI
2001
13 years 7 months ago
Robot Weightlifting By Direct Policy Search
This paper describes a method for structuring a robot motor learning task. By designing a suitably parameterized policy, we show that a simple search algorithm, along with biologi...
Michael T. Rosenstein, Andrew G. Barto
ICRA
2008
IEEE
169views Robotics» more  ICRA 2008»
14 years 6 days ago
Sparse incremental learning for interactive robot control policy estimation
— We are interested in transferring control policies for arbitrary tasks from a human to a robot. Using interactive demonstration via teloperation as our transfer scenario, we ca...
Daniel H. Grollman, Odest Chadwicke Jenkins
ICRA
2010
IEEE
145views Robotics» more  ICRA 2010»
13 years 4 months ago
Reinforcement learning of motor skills in high dimensions: A path integral approach
— Reinforcement learning (RL) is one of the most general approaches to learning control. Its applicability to complex motor systems, however, has been largely impossible so far d...
Evangelos Theodorou, Jonas Buchli, Stefan Schaal