A Weighted Technique in Heuristic Search

As shown in [1], we examine s e a r c h as a s t a t i s t i c s a m p l i n g p r o c e s s . Based o n some s t a t i s t i c a l i n f e r e n c e method t h e p r o b a b i l i t y t h a t a s u b t r e e i n s e a r c h t r e e c o n t a i n s t h e g o a l can b e d e c i d e d . Thus some w e i g h t i s i n t e n t i o n a l y added t o t h e e v a l u a t i o n f u n c t i o n o f t h o s e nodes w h i c h a r e u n l i k e l y i n t h e s o l u t i o n p a t h s o t h a t t h e s e a r c h w i l l c o n c e n t r a t e o n t h e most p r o m i s i n g p a t h . I t r e s u l t s i n a new w e i g h t e d a l g o r i t h m W S A . Tn a u n i f o r m m-ary t r e e , we show t h a t a g o a l can be f o u n d by WSA in t h e p o l y n o m i a l t i m e , a l t h o u g h t h e c o m p u t a t i o n a l c o m p l e x i t y o f A ( o r A*) may be 0 ( e ) f o r s e a r c h i n g t h e same s p a c e . Where N i s t h e d e p t h a t w h i c h t h e g o a l i s l o c a t e d .