CMAC application using triangulation in reinforcement learning
基于三角剖分的小脑模型在增强学习中的应用

A reinforcement learning controller based on CMAC neural networks using triangulation was studied and applied to the learning control of intercepting a ball in the RoboCup.By utilizing Kuhn triangulation based on simplex interpolation in the continuous state space of Markov Decision Processes(MDPs),the value functions of MDPs were approximated with linear triangulation so that the generalization ability of the CMAC-based reinforcement learning controller could be improved.Simulation results on the learning ...