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CDC
2009
IEEE
132views Control Systems» more  CDC 2009»
15 years 11 months ago
Q-learning and Pontryagin's Minimum Principle
Abstract— Q-learning is a technique used to compute an optimal policy for a controlled Markov chain based on observations of the system controlled using a non-optimal policy. It ...
Prashant G. Mehta, Sean P. Meyn
ICRA
2010
IEEE
145views Robotics» more  ICRA 2010»
15 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
ISCAS
2007
IEEE
104views Hardware» more  ISCAS 2007»
16 years 20 days ago
Evaluation of Algorithms for Low Energy Mapping onto NoCs
—Systems on Chip (SoCs) congregate multiple modules and advanced interconnection schemes, such as networks on chip (NoCs). One relevant problem in SoC design is module mapping on...
César A. M. Marcon, Edson I. Moreno, Ney La...
HIPEAC
2010
Springer
15 years 4 months ago
Buffer Sizing for Self-timed Stream Programs on Heterogeneous Distributed Memory Multiprocessors
Abstract. Stream programming is a promising way to expose concurrency to the compiler. A stream program is built from kernels that communicate only via point-to-point streams. The ...
Paul M. Carpenter, Alex Ramírez, Eduard Ayg...
ALT
2007
Springer
16 years 3 months ago
Learning Rational Stochastic Tree Languages
Abstract. We consider the problem of learning stochastic tree languages, i.e. probability distributions over a set of trees T(F), from a sample of trees independently drawn accordi...
François Denis, Amaury Habrard