1. A method for reinforcement learning, the method comprising: in a neural network comprising multiple neurons and multiple noruens interconnected by multiple synapse devices: receiving a reinforcement signal resulting from a neuron and a noruen of the neural network spiking together, wherein the noruen comprises a symmetric dual of the neuron, the neuron and the noruen spike together repeatedly, the reinforcement signal corresponds to an event involving an action, and the reinforcement signal represents a reward indicating success of the action; and determining at least one synapse device of the multiple synapse devices contributing to the spiking of the neuron and the noruen; and selectively updating synaptic weights of the multiple synapse devices to strengthen the at least one synapse device determined, wherein the updated synaptic weights allows selection of at least one action that increases rewards over time.