1. A neural network for reinforcement-learning and for action-selection comprising: a plurality of channels; a population of input neurons in each of the channels; a population of output neurons in each of the channels, each population of input neurons in each of the channels coupled to each population of output neurons in each of the channels by first synapses; and a population of reward neurons in each of the channels, wherein each population of reward neurons receives input from an environmental input, and wherein each channel of reward neurons is coupled only to output neurons in a channel that the reward neuron is part of by second synapses; wherein if the environmental input for a channel is positive, the corresponding channel of a population of output neurons are rewarded and have their responses reinforced; wherein if the environmental input for a channel is negative, the corresponding channel of a population of output neurons are punished and have their responses attenuated; and wherein the neural network comprises memristors.