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This paper proposes a new reinforcement learning algorithm called TD-GNG that uses the Growing Neural Gas (GNG) network to deal with environments of large domains. The proposed algorithm is capable to reduce the dimensionality of the problem by aggregating similar states. In experimental comparison against tile-coding in mountain car and puddle world, the TD-GNG showed an increase in the generalization...
This work describes an award winning approach for solving the NN3 Forecasting Competition problem, focusing on the sound experimental validation of its main innovative feature. The NN3 forecasting task consisted of predicting 18 future values of 111 short monthly time series. The main feature of the approach was the use of the median for combining the forecasts of an ensemble of 15 MLPs to predict...
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