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JMLR
2010
148views more  JMLR 2010»
13 years 2 months ago
A Generalized Path Integral Control Approach to Reinforcement Learning
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
Evangelos Theodorou, Jonas Buchli, Stefan Schaal
ML
1998
ACM
101views Machine Learning» more  ML 1998»
13 years 7 months ago
Elevator Group Control Using Multiple Reinforcement Learning Agents
Recent algorithmic and theoretical advances in reinforcement learning (RL) have attracted widespread interest. RL algorithmshave appeared that approximatedynamic programming on an ...
Robert H. Crites, Andrew G. Barto
ICRA
2008
IEEE
128views Robotics» more  ICRA 2008»
14 years 1 months ago
Intrinsically motivated hierarchical manipulation
— We present a framework for the programming of manipulation behavior by means of an intrinsic reward function that encourages the building of deep control knowledge. We show how...
Stephen Hart, Shijaj Sen, Roderic A. Grupen
CDC
2010
IEEE
105views Control Systems» more  CDC 2010»
13 years 2 months ago
Learning in mean-field oscillator games
This research concerns a noncooperative dynamic game with large number of oscillators. The states are interpreted as the phase angles for a collection of non-homogeneous oscillator...
Huibing Yin, Prashant G. Mehta, Sean P. Meyn, Uday...
ILP
2007
Springer
14 years 1 months ago
Structural Statistical Software Testing with Active Learning in a Graph
Structural Statistical Software Testing (SSST) exploits the control flow graph of the program being tested to construct test cases. Specifically, SSST exploits the feasible paths...
Nicolas Baskiotis, Michèle Sebag