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ATAL
2005
Springer
14 years 29 days 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
IJCAI
2007
13 years 8 months ago
Constructing New and Better Evaluation Measures for Machine Learning
Evaluation measures play an important role in machine learning because they are used not only to compare different learning algorithms, but also often as goals to optimize in cons...
Jin Huang, Charles X. Ling
GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
13 years 11 months ago
On-line evolutionary computation for reinforcement learning in stochastic domains
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
Shimon Whiteson, Peter Stone
SSPR
2004
Springer
14 years 22 days ago
Structures of Covariance Matrix in Handwritten Character Recognition
The integrated approach is a classifier established on statistical estimator and artificial neural network. This consists of preliminary data whitening transformation which provide...
Sarunas Raudys, Masakazu Iwamura
KES
2007
Springer
13 years 7 months ago
An Application of Machine Learning Methods to PM10 Level Medium-Term Prediction
The study described in this paper, analyzed the urban and suburban air pollution principal causes and identified the best subset of features (meteorological data and air pollutants...
Giovanni Raimondo, Alfonso Montuori, Walter Moniac...