Li Yongcheng, Sun Rong, Zhang Bin, Wang Yuechao, Li Hongyi
State Key Laboratory of Robotics, Shenyang Institute of Automation, University of Chinese Academy of Sciences, Shenyang, Liaoning, P. R. China.
Hefei National Laboratory for Physical Sciences at the Microscale, Hefei, Anhui, P. R. China.
PLoS One. 2015 May 19;10(5):e0127452. doi: 10.1371/journal.pone.0127452. eCollection 2015.
Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.
神经网络被认为是生物体智能的起源。在本文中，创建了一种将生物智能与人工智能融合的智能系统新设计。它基于一个与实际移动机器人双向连接的神经控制器，以实现一种新型车辆。两种类型的实验制剂被用作神经控制器，包括“随机”和“4Q”（人工分为四个相互连接部分的培养神经元）神经网络。与随机培养物相比，“4Q”培养物呈现出完全不同的活动，并且由“4Q”网络控制的机器人在搜索任务中表现出更好的能力。我们的结果表明，神经培养物可以成功用于控制人工代理；由于短期可塑性，机器人在刺激下表现得越来越好。提供了一个新的框架来研究双向生物 - 人工接口，并使用这些简化的模型系统为未来的智能系统开发新策略。
