Domain-Dependent Single-Agent Search Enhancements

  title={Domain-Dependent Single-Agent Search Enhancements},
  author={Andreas Junghanns and Jonathan Schaeffer},
Al research has developed an extensive collect ion of methods to solve state-space problems. Using the challenging domain of Sokoban, this paper studies the effect of search enhancements on program performance. We show that the current state of the ar t in AT generally requires a large p rog ramming and research effort into domain-dependent: methods to solve even moderately complex problems in such di f f icul t domains. The appl icat ion of domain-specif ic knowledge to exploi t propert ies of… CONTINUE READING
Highly Cited
This paper has 56 citations. REVIEW CITATIONS


Publications citing this paper.

57 Citations

Citations per Year
Semantic Scholar estimates that this publication has 57 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-9 of 9 references

Searching w i t h pa t te rn databases

J. Culberson, J. Schaeffer
G. McCal la , edi tor , Advances in Artificial Intelligence, pages 402-416. Springer-Verlag • 1996
View 4 Excerpts
Highly Influenced

Relevance Cuts: Localizing the Search

Computers and Games • 1998
View 9 Excerpts
Highly Influenced


R. E. Kor f . F ind ing op t ima l solut ions to Rub databases
pages 700 705, • 1997

Technical Report T R 9 7 - 0 2

J. Culberson. Sokoban is PSPACEcornplete
Dept. of C o m p u t i n g Science, Universi ty of A lber ta , • 1997
View 1 Excerpt

Pushing the envelope: p lann ing

I I . Kau tz, B. Selman
proposi t ional logic and stochastic search. In AAAI, pages 1194-1201, • 1996

B1DA* : An improved per imeter search a lgo r i t hm

G. Manz in i
Artificial Intelligence, 75:347-360, • 1995
View 1 Excerpt


U D. Dor
S O K O B A N and other mot ion p lann ing problems, • 1995
View 1 Excerpt