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» Optimization via Parameter Mapping with Genetic Programming
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ATAL
2005
Springer
14 years 2 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
GECCO
2007
Springer
165views Optimization» more  GECCO 2007»
14 years 2 months ago
Peptide detectability following ESI mass spectrometry: prediction using genetic programming
The accurate quantification of proteins is important in several areas of cell biology, biotechnology and medicine. Both relative and absolute quantification of proteins is often d...
David C. Wedge, Simon J. Gaskell, Simon J. Hubbard...
EUROGP
2010
Springer
167views Optimization» more  EUROGP 2010»
13 years 9 months ago
An Analysis of Genotype-Phenotype Maps in Grammatical Evolution
We present an analysis of the genotype-phenotype map in Grammatical Evolution (GE). The standard map adopted in GE is a depth-first expansion of the non-terminal symbols during the...
David Fagan, Michael O'Neill, Edgar Galván ...
ICCAD
1997
IEEE
112views Hardware» more  ICCAD 1997»
14 years 25 days ago
Circuit optimization via adjoint Lagrangians
The circuit tuning problem is best approached by means of gradient-based nonlinear optimization algorithms. For large circuits, gradient computation can be the bottleneck in the o...
Andrew R. Conn, Ruud A. Haring, Chandramouli Viswe...
CDC
2008
IEEE
145views Control Systems» more  CDC 2008»
14 years 3 months ago
Parameter estimation with expected and residual-at-risk criteria
In this paper we study a class of uncertain linear estimation problems in which the data are affected by random uncertainty. In this setting, we consider two estimation criteria,...
Giuseppe Carlo Calafiore, Ufuk Topcu, Laurent El G...