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» Approximation algorithms for stochastic orienteering
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NIPS
2007
13 years 10 months ago
Incremental Natural Actor-Critic Algorithms
We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic reinforcement learning m...
Shalabh Bhatnagar, Richard S. Sutton, Mohammad Gha...
ICANN
2010
Springer
13 years 9 months ago
Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines
Abstract. Learning algorithms relying on Gibbs sampling based stochastic approximations of the log-likelihood gradient have become a common way to train Restricted Boltzmann Machin...
Asja Fischer, Christian Igel
CHARME
1997
Springer
105views Hardware» more  CHARME 1997»
14 years 7 days ago
Simulation-based verification of network protocols performance
Formal verification techniques need to deal with the complexity of the systems rified. Most often, this problem is solved by taking an abstract model of the system and aiming at a...
Mario Baldi, Fulvio Corno, Maurizio Rebaudengo, Pa...
NIPS
1996
13 years 10 months ago
Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning
Model learning combined with dynamic programming has been shown to be e ective for learning control of continuous state dynamic systems. The simplest method assumes the learned mod...
Jeff G. Schneider
CDC
2010
IEEE
122views Control Systems» more  CDC 2010»
13 years 3 months ago
Nonholonomic source seeking in switching random fields
We consider the problem of designing controllers for nonholonomic mobile robots converging to the source (minimum) of a field. In addition to the mobility constraints posed by the ...
Shun-ichi Azuma, Mahmut Selman Sakar, George J. Pa...