多阶段区间模糊决策问题的λ模糊启发式搜索算法IFDA

Interval fuzzy multi-stage decision problems

提出了多阶段区间模糊决策问题的自底向上的λ模糊启发式搜索算法IFDA ,并证明了只要启发式估价函数h可采纳 ,则IFDA 算法亦可采纳 ,且定能找到具有最小耗散的最佳决策序列 ,对于可采纳启发式估价函数h通常难以设计这一问题 ,提出了启发式估价函数的渐进式学习算法Learning h.证明了通过IFDA 算法的大量解 ,Learning h算法能以概率为 1使启发式估价函数学习并收敛为可采纳的启发式估价函数。

Fuzzy backward heuristic search algorithm IFDA * was presented for interval fuzzy multi stage decision problems. It was proved that with admissible heuristic evaluation function h, IFDA * algorithm is admissible and can always find out the best decision sequence with minimal cost. In terms of the fact that in general an admissible h is very difficult to design, the asymptotic learning algorithm for learning h was also presented. Learning h algorithm has a very important characteristic that as more is learned during IFDA * algorithm(s problem solving, with probability 1, Learning h algorithm can make a heuristic evaluation function converge to an admissible one.