A New Approach of Iterative Deepening Bi- Directional Heuristic Front-to-Front Algorithm (IDBHFFA)

摘要: Artificial Intelligence (AI) is a subject that studies techniques for making computers exhibit intelligent behavior. S earching still remains one of the problem in AI. Bi -directional search performed by searching simultaneously forward direction from initial node and backward goal node. Bi-directional heuristic algorithms need less time space than their unidirectional versions. Heuristic Front to Algorithm (BHFFA) - directional algorithm. However, it has some disadvantages. It needs store many unnecessary nodes prior termination. Moreover, large spaces computational overhead selection next be expanded increases significantly. This paper presents modification BHFFA called Iterative Deepening Front-to-Front (IDBHFFA) been analyzed implemented using 8-puzzle problem. The proposed algorithm performs number iterations. For each iteration, two thresholds are maintained, frontier. In non-promising on particular frontier having cost estimates greater corresponding threshold value pruned. process continues with successive iterations increasing iteration. will return optimal solutions an admissible function. can minimize memory requirement considerably.