Analyzing uninformed search strategy algorithms in state space search

2016 ◽  
Author(s):  
S Pooja ◽  
S Chethan ◽  
C V Arjun
Keyword(s):  
State Space ◽  
Search Strategy ◽  
State Space Search

scholarly journals The FF Planning System: Fast Plan Generation Through Heuristic Search

2001 ◽  
Vol 14 ◽  
pp. 253-302 ◽  
Author(s):  
J. Hoffmann ◽  
B. Nebel
Keyword(s):  
State Space ◽  
Heuristic Search ◽  
Search Strategy ◽  
Search Space ◽  
Systematic Search ◽  
Hill Climbing ◽  
Planning System ◽  
Plan Generation ◽  
State Space Search ◽  
Algorithmic Techniques

We describe and evaluate the algorithmic techniques that are used in the FF planning system. Like the HSP system, FF relies on forward state space search, using a heuristic that estimates goal distances by ignoring delete lists. Unlike HSP's heuristic, our method does not assume facts to be independent. We introduce a novel search strategy that combines hill-climbing with systematic search, and we show how other powerful heuristic information can be extracted and used to prune the search space. FF was the most successful automatic planner at the recent AIPS-2000 planning competition. We review the results of the competition, give data for other benchmark domains, and investigate the reasons for the runtime performance of FF compared to HSP.

Heuristics for Domain-Independent Planning: A Survey

2011 ◽  
Vol 135-136 ◽  
pp. 573-577 ◽  
Author(s):  
Rui Shi Liang ◽  
Min Huang
Keyword(s):  
State Space ◽  
Heuristic Search ◽  
Research Work ◽  
Future Research ◽  
Survey Analysis ◽  
Work Related ◽  
State Space Search ◽  
Survey Results ◽  
Domain Independent ◽  
Intense Research

Increasing interest has been devoted to Planning as Heuristic Search over the years. Intense research has focused on deriving fast and accurate heuristics for domain-independent planning. This paper reports on an extensive survey and analysis of research work related to heuristic derivation techniques for state space search. Survey results reveal that heuristic techniques have been extensively applied in many efficient planners and result in impressive performances. We extend the survey analysis to suggest promising avenues for future research in heuristic derivation and heuristic search techniques.

Multiobjective State Space Search

1999 ◽  
pp. 19-48
Author(s):  
Pallab Dasgupta ◽  
P. P. Chakrabarti ◽  
S. C. DeSarkar
Keyword(s):  
State Space ◽  
State Space Search
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