模拟昆虫视觉-行为抉择的强化学习模型

视觉信息用于行为抉择的过程是一个极其复杂的脑信息处理过程,昆虫或动物对外界环境的学习是以价值来控制的,并可影响其行为抉择,研究这一过程对揭示人类自身脑运行机制有重要意义.文章在郭爱克研究小组果蝇实验提供的生物依据基础上,提出了一种模拟果蝇视觉-行为抉择的神经网络模型.该模型引入了价值和基于价值的强化学习算法,应用于输入视觉图像的强化学习,以此建立果蝇脑内多巴胺和蘑菇体对于抉择判断的价值体系.模拟的结果表明,该模型可以模拟果蝇视觉信息的学习和行为抉择过程,其结果与生物实验相符,同时也为机器人视觉信息控制行为抉择的应用提供了基础.

A Reinforcement Learning Model to Simulate Insect’s Choice Behavior Facing Visual Cues

Choice behavior based on visual cues is a very complicated information process of brain. Biological experiments showed that learning of insects or animals in the environment is controlled by value system which affects their choice behavior. This study is significant to reveal the mechanism of human brain. A neural network model was proposed to simulate the choice behavior of insects facing visual cues based on biological facts of Guo's group. The proposed model introduces value system and a reinforcement learning algorithm based on the value system. It can learn input visual images under the reward or punishment and establish a value system, which simulates choice behavior based on dopamine and mushroom body circuit in the brain of insects. The simulation results show that the proposed model can simulate the development of value system and choice behavior of drosophila. The simulating curves accord with biological experiments. This model provides a basis for the further application on robot auto-control system facing visual cues.