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Neural networks and learning with delayed reinforcement
RAMbased nodes and networks
6 other sections not shown
ablation action activity ADB system addressed Aleksander animal learning Artificial Neural Networks associated attention attention-setting average backpropagation Barto behaviour bits Boycott and Young brain cells chapter classical conditioning crab crab-plus-square cycles decay defined delay learning delay to attack delayed reinforcement discrimination elicit Equation example experiments exploratory learning external input hippocampus implemented input pattern input-output pair involves judge module layer learnable learning system locj[addj look-up table machine memory units move Myers n-tuple negative patterns negative reinforcement neurons node output object occurs octopus optic lobe output function OVSIM parameters positive patterns positive reinforcement possible pRAM predict probabilistic probabilistic logic probability of attack problem RAM-based nodes random receptive field reinforcement arrives reinforcement learning response result SFVL short-term memory shown in Figure shows simulations stored values supervised learning temporal difference trained patterns training set trials unspecific effect vertical lobe visual VMAX vote