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自律个体的遗传强化模型是模拟实际生物进化机制的计算模型．本文利用进化算法和人工神经网络的研究方法，设计了一种自律个体的遗传强化模型．该模型强调多层次学习，实现了先天的遗传学习进化和后天的个体神经系统学习进化的有机结合．本文同时将该模型应用于模拟机器人的生存控制，观察它在环境中的行为表现及进化能力，取得了满意的实验结果．
The self-disciplined genetic enhancement model is a computational model that simulates the actual biological evolution mechanism. In this paper, we use the research methods of evolutionary algorithm and artificial neural network to design a genetic enhancement model of autonomous individuals. The model emphasizes multilevel learning, and realizes the organic combination of innate genetic learning evolution and the acquired individual nervous system learning evolution. In the meantime, this model is applied to simulate the survival control of robots and observe its behavior in the environment and its evolutionary ability. Satisfactory experimental results have been obtained.