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CDC
2010
IEEE
136views Control Systems» more  CDC 2010»
13 years 2 months ago
Pathologies of temporal difference methods in approximate dynamic programming
Approximate policy iteration methods based on temporal differences are popular in practice, and have been tested extensively, dating to the early nineties, but the associated conve...
Dimitri P. Bertsekas
NIPS
1994
13 years 9 months ago
Generalization in Reinforcement Learning: Safely Approximating the Value Function
To appear in: G. Tesauro, D. S. Touretzky and T. K. Leen, eds., Advances in Neural Information Processing Systems 7, MIT Press, Cambridge MA, 1995. A straightforward approach to t...
Justin A. Boyan, Andrew W. Moore
AMC
2007
115views more  AMC 2007»
13 years 7 months ago
Evolutionary programming based on non-uniform mutation
Abstract–A new evolutionary programming algorithm (NEP) using the non-uniform mutation operator instead of Gaussian or Cauchy mutation operators is proposed. NEP has the merits o...
Xinchao Zhao, Xiao-Shan Gao, Ze-Chun Hu
GLVLSI
2006
IEEE
185views VLSI» more  GLVLSI 2006»
14 years 1 months ago
Application of fast SOCP based statistical sizing in the microprocessor design flow
In this paper we have applied statistical sizing in an industrial setting. Efficient implementation of the statistical sizing algorithm is achieved by utilizing a dedicated interi...
Murari Mani, Mahesh Sharma, Michael Orshansky
NIPS
2007
13 years 9 months ago
Receding Horizon Differential Dynamic Programming
The control of high-dimensional, continuous, non-linear dynamical systems is a key problem in reinforcement learning and control. Local, trajectory-based methods, using techniques...
Yuval Tassa, Tom Erez, William D. Smart