Abstract
With the development of artificial intelligence, the mainstream neural networks currently have many insurmountable problems, such as a large amount of calculation, high power consumption, and low intelligence. In order to solve the above problems, the spiking neural network simulates creating the brain according to the characteristics of the human brain, and realizes intelligence with a neural network close to that of a living being. This article uses biological causality to creatively propose a multi-layered spiking neural network structure with universality, and a learning algorithm for spiking neural network, and apply it to poker games, so that the poker robot can learn a person's card ability The ultimate degree of personification was 85%, which verified the feasibility of the structure and algorithm of impulsive neural network.
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