针对基于普通发育算法实现机器人视觉定位任务时需分配大量神经元的问题,提出一种基于单胺类神经递质调节发育算法的机器人视觉定位方法。首先引入在脑内控制多种生理功能的多巴胺(dopamine)与5-羟色胺(serotonin)的单胺类神经递质理论,实现神经调节作用;然后结合普通发育算法,建立基于神经递质调节的发育算法。机器人采用自主试错策略完成强化学习过程,存储“记忆”,并可动态改变学习速率,最终实现视觉定位任务。实验结果证明该方法仅需提前配置与所需相关知识概念个数相同数量的神经元,显著减少了所需神经元数量,提高算法效率。
A robot vision location based on developmental algorithm of monoamine neurotransmitters modulation is pro-posed to solve the problem that a large number of neurons need to be allocated in vision location task based on general developmental algorithms. Firstly, the monoamine neurotransmitter theory of dopamine and serotonin controlling a vari-ety of physiological functions in the brain is introduced to realize neural modulation. Then, the developmental algorithm of monoamine neurotransmitters modulation is established based on general developmental algorithms. The robot uses au-tonomous trial and error strategies to complete the process of reinforcement learning, store “memory”, and dynamically change the learning rate, and ultimately it realizes vision location task. Experimental results show that the number of neu-rons to be allocated in advance in the proposed method is as few as the number of required knowledge concepts, which can significantly reduce the required number of neurons and increase algorithm efficiency.