加快启发式实时算法的收敛

Speeding up the Convergence of Real-time Search Through Changing Value-update Rules

LRTA 算法是一种实时搜索算法 ,若重复求解同样的规划任务 ,LRTA 将收敛于最短路径 .文中给出了通过改变值更新规则来加快实时算法收敛的一种方法 .实验表明它比LRTA

Learning Real time A *(LRTA *)is a real time search algorithm which converges to the shortest path when it solves the same planning task repeatedly. The method to speed up its convergence through change value update rules is proposed.The experiment shows that it often converges suboptimal solution faster than LRTA *.