Delay Learning in Artificial Neural Networks |
Contents
Neural networks and learning with delayed reinforcement | 12 |
RAMbased nodes and networks | 29 |
Attentiondriven buffering | 62 |
Copyright | |
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ablation accept action ADB system addressed Aleksander algorithm animal learning Artificial Neural Networks associated attention attention-setting Barto behaviour bits Boycott and Young brain cells chapter classical conditioning cortex crab crab-plus-square decay decision delay learning delay to attack detectors discrimination elicit Equation example experiments exploratory learning feature hippocampus horizontal images implemented increases input pattern involves learn to reject learnable learning system memory units module Myers n-tuple negative patterns negative reinforcement neurons node node output object occur operant conditioning tasks optic lobe output function OVSIM parameters positive and negative positive patterns positive reinforcement possible predict probabilistic logic probability of attack problem Proc processing RAM-based nodes random receptive field reinforcement arrives reinforcement learning result short-term memory shown in Figure shows simulations stimulus pattern stored value supervised learning tendency to attack trained patterns training set transfer of learned trials unspecific effect vertical lobe VMAX vote