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Learning in Embedded Systems explores algorithms that learn efficiently from trial-and error experience with an external world. It is the first detailed exploration of the problem of learning action strategies in the context of designing embedded systems that adapt their behavior to a complex, changing environment.

 
 

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Thomas Poutas in exclusive Partnership for Greece, Germany and Austria offers the fastest Business Intelligence Solution for Retail Performance Management.

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Adhension reference

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