改进的模糊Sarsa学习

An Improved Fuzzy Sarsa Learning

为了解决模糊Sarsa学习(FSL)无法在线自适应调节学习因子和不能处理学习过程中探索与利用的平衡问题,提出了一种改进的模糊Sarsa学习(IFSL)算法.在FSL基础上,引入自适应学习率产生器来在线调节学习因子,增加模糊平衡器控制探索和利用的程度.给出了IFSL的结构框图,证明了IFSL中可调节权向量具有平衡不动点.仿真结果表明,与FSL相比,IFSL能加快系统的学习收敛速度,具有较好的学习性能.

It is difficult for fuzzy Sarsa learning（FSL） to tune learning rate and balance exploration vs. exploitation, so an improved FSL（IFSL） method based on FSL is presented. In the method, an adaptive learning rate generator for tuning learning rate on-line and a fuzzy balaneer for controlling the degree of exploration vs. exploitation are introduced. The diagram of IFSL is given, and the weight vector of IFSL with stationary action selection policy converges to a unique value is proved. Simulation results show that IFSL well manager balance, and outperforms FSL in terms of learning speed and action quality.