TY - GEN

T1 - NSA algorithm and its computational complexity - Preliminary results

AU - Zhang, Weixiong

PY - 1989

Y1 - 1989

N2 - To overcome the limitations of the model of statistical heuristic search, the author proposes the idea of combining nonparametric statistical inference methods with the heuristic search. A nonparametric statistical heuristic search algorithm (NSA) is presented, and its computational complexity is discussed. It is shown that, in a uniform m-ary search tree G with a single goal SN located at an unknown site in the N-th depth, NSA can find the goal asymptotically with probability one, and the complexity remains O(N(ln N)2), where N is the length of the solution path.

AB - To overcome the limitations of the model of statistical heuristic search, the author proposes the idea of combining nonparametric statistical inference methods with the heuristic search. A nonparametric statistical heuristic search algorithm (NSA) is presented, and its computational complexity is discussed. It is shown that, in a uniform m-ary search tree G with a single goal SN located at an unknown site in the N-th depth, NSA can find the goal asymptotically with probability one, and the complexity remains O(N(ln N)2), where N is the length of the solution path.

UR - http://www.scopus.com/inward/record.url?scp=0024883961&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0024883961

SN - 0818619848

T3 - IEEE Int Workshop Tools Artif Intell Archit Lang Algorithms

SP - 442

EP - 446

BT - IEEE Int Workshop Tools Artif Intell Archit Lang Algorithms

A2 - Anon, null

PB - Publ by IEEE

T2 - IEEE International Workshop on Tools for Artificial Intelligence: Architectures, Languages and Algorithms

Y2 - 23 October 1989 through 25 October 1989

ER -