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138
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IROS
2007
IEEE
168views Robotics» more  IROS 2007»
15 years 9 months ago
Improving humanoid locomotive performance with learnt approximated dynamics via Gaussian processes for regression
Abstract— We propose to improve the locomotive performance of humanoid robots by using approximated biped stepping and walking dynamics with reinforcement learning (RL). Although...
Jun Morimoto, Christopher G. Atkeson, Gen Endo, Go...
134
Voted
CLUSTER
2004
IEEE
15 years 3 months ago
Performance Evaluation of Shared Mesh Protection in WDM Networks
The efficient use of network capacity in shared restoration schemes strongly depends upon the path selection procedure. In this paper we propose and evaluate path selection algorit...
Chadi Assi, Ahmad Khalil, Nasir Ghani, Abdallah Sh...
166
Voted
ECUMN
2004
Springer
15 years 7 months ago
Multi-time-Scale Traffic Modeling Using Markovian and L-Systems Models
Traffic engineering of IP networks requires the characterization and modeling of network traffic on multiple time scales due to the existence of several statistical properties that...
Paulo Salvador, António Nogueira, Rui Valad...
184
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JMLR
2010
148views more  JMLR 2010»
14 years 10 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
127
Voted
EVOW
2003
Springer
15 years 8 months ago
Landscape State Machines: Tools for Evolutionary Algorithm Performance Analyses and Landscape/Algorithm Mapping
Abstract. Many evolutionary algorithm applications involve either fitness functions with high time complexity or large dimensionality (hence very many fitness evaluations will typi...
David Corne, Martin J. Oates, Douglas B. Kell