“School of Cognitive Sciences”
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| Paper IPM / Cognitive Sciences / 7519 |
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Bounded rationality and satisfying models rather than optimization techniques have shown good performance in decision making. The emotional learning algorithm is such a method based on reinforcement agents emulating the emotional cues in human. A new approach towards purposeful prediction problems, derived from a recently developed model of emotional learning in human brain, is introduced in this paper. The proposed algorithm inherently emphasizes on learning to predict the high values of inputs and performs remarkably accurate predictions among the important regions, features or objectives. Space weather forecasting in an excellent case of using this methodology and in fact was the motivation to introduce the purposeful prediction via multi objective learning algorithms in this research. Three examples of predicting the solar activity, geomagnetic activity and geomagnetic storms show the characteristics of the proposed algorithm and its usefulness to space weather warning and alert systems.
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