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Statistical Models of Conditioning

 Peter Dayan and Theresa Long
  
 

Abstract:
Recent evidence suggests that dopaminergic neurons in vertebrates report prediction errors during reward based classical and instrumental conditioning. We consider more complicated conditioning paradigms which involve combining predictions from multiple predictive stimuli. We show that our existing model fails to act in accordance with the learning data, and suggest an alternative in which there is attentional selection between different available stimuli. The new model is a form of mixture of experts (Jacobs, Jordan & Barto, 1991) and is statistically well-founded.

 
 


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