Applied-Information Technology and Parallel Learning Rules in Intelligent Control System
Wei Qiong Ye, Kai Li Cheng, Lin Xu · Advanced materials research · 2014
This paper applied information technology and takes the exploratory action or state transfer formed experiences of control system as the basis, in the unsupervised condition obtaining planning and controlling rules from experiences as the control knowledge. In learning process, experiences will deduce to rules, then generate high-level concepts or rules, constitute multi-resolution knowledge architecture. In the experiment, mobile robot effective learning and planning system state and action control in quasi-optimal manner based with random experiences.