This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Enhanced Iterative-Deepening Search
July 1994 (vol. 16 no. 7)
pp. 701-710

Iterative-deepening searches mimic a breadth-first node expansion with a series of depth-first searches that operate with successively extended search horizons. They have been proposed as a simple way to reduce the space complexity of best-first searches like A* from exponential to linear in the search depth. But there is more to iterative-deepening than just a reduction of storage space. As the authors show, the search efficiency can be greatly improved by exploiting previously gained node information. The information management techniques considered here owe much to their counterparts from the domain of two-player games, namely the use of fast-execution memory functions to guide the search. The authors' methods not only save node expansions, but are also faster and easier to implement than previous proposals.

[1] S. G. Akl and M. M. Newborn, "The principal continuation and the killer heuristic," inProc. ACM Nat. Conf., Seattle, WA, 1977, pp. 466-473.
[2] P. P. Chakrabarti, S. Ghose, A. Acharya, and S. C. de Sarkar, "Heuristic search in restricted memory,"Artificial Intell., vol. 41, no. 2, pp. 197-221, Dec. 1989.
[3] P. E. Hart, N. J. Nilsson and B. Raphael, "A formal basis for the heuristic determination of minimum cost paths,"IEEE Trans. Syst. Sci. Cybern., vol. SSC-4, no. 2, pp. 100-107, 1968.
[4] M. Held and R. M. Karp, "The traveling salesman problem and minimal spanning trees,"Operat. Res., vol. 18, pp. 1138-1162, 1970.
[5] M. Held and R. M. Karp, "The traveling salesman problem and minimal spanning trees: Part II,"Math. Progr., vol. 1, 6-25, 1971.
[6] T. Ibaraki, "The power of dominance relations in branch-and-bound algorithms,"J. ACM, vol. 24, no. 2, pp. 264-279, 1977.
[7] T. Ibaraki, "Depth-msearch in branch-and-bound algorithms,"Int. J. Comput. and Inform. Sci., vol. 7, no. 4, pp. 315-343, 1978.
[8] R. E. Korf, "Depth-first iterative deepening: An optimal admissible tree search,"Artificial Intell., vol. 25, pp. 97-109, 1985.
[9] T.D.C. Little and A. Ghafoor, "Network Considerations for Distributed Multimedia Object Composition and Communication,"IEEE Network, Vol. 4, No. 6, Nov. 1990, pp. 32-49.
[10] J. D. C. Little, K. G. Murty, D. W. Sweeney and G. Karel, "An algorithm for the traveling salesman problem,"Operat. Res., vol. 11, pp. 972-989, 1963.
[11] A. Mahanti, S. Ghosh, D. S. Nau, A. K. Pal, and L. Kanal, "Performance of IDA* on trees and graphs," in10th Nat. Conf. on Artificial Intell., AAAI-92, San Jose, CA, 1992, pp. 539-544.
[12] A. Mahanti, D. S. Nau, S. Ghosh, and L. Kanal, "An efficient iterative threshold heuristic search algorithm," Univ. of Maryland, College Park, Tech. Rep. CS-TR-2853, 1992.
[13] T. A. Marsland, "Computer chess methods," inEncyclopedia of Artificial Intelligence, 1st ed., E. Shapiro, Ed. New York: Wiley, 1987, pp. 159-171. See also, "Computer chess and search," inEncyclopedia of Artificial Intelligence, 2nd ed., 1992, pp. 224-241.
[14] T. A. Marsland, A. Reinefeld, and J. Schaeffer, "Low overhead alternatives to SSS*,"Artificial Intell., vol. 31, no. 2, pp. 185-199, 1987.
[15] B. G. Patrick, "Binary iterative-deepening A*: An admissible generalization of IDA* search," inProc. 9th Canadian Conf. on Artificial Intell. AI'92, Vancouver, BC, 1992, pp. 54-59.
[16] J. Pearl,Heuristics: Intelligent Search Strategies for Computer Problem Solving. Reading, Mass: Addison-Wesley, 1984.
[17] C. Powley and R. E. Korf, "Single-agent parallel window search,"IEEE Trans. Pattern Anal. Machine Intell., vol. 13, no 5, pp. 466-477, May 1991.
[18] V. N. Rao, V. Kumar, and R. E. Korf, "Depth-first vs. best-first search," inProc. 9th Nat. Conf. on Artificial Intell. AAAI-91, Anaheim, CA, 1991, pp. 434-440.
[19] A. Reinefeld, J. Schaeffer, and T. A. Marsland, "Information acquisition in minimal window search," inProc. 9th Int. Joint Conf. on Artificial Intell., France, 1985, pp. 1040-1043.
[20] A. Reinefeld, "Complete solution of the Eight-Puzzle and the benefit of node ordering in IDA*," inProc. 13th Int. Joint Conf. on Artificial Intell., Chambéry, 1993, pp. 248-253.
[21] S. Russell, "Efficient memory-bounded search methods," inProc. European Artificial Intell. Conf., Vienna, 1992, pp. 1-5.
[22] U. K. Sarkar, P. P. Chakrabarti, S. Ghose, and S. C. de Sarkar, "Reducing re-expansions in iterative-deepening search by controlling cutoff bounds,"Artificial Intell., vol. 50, pp. 207-221, 1991.
[23] J. Schaeffer, "The history heuristic and alpha-beta search enhancements in practice,"IEEE Trans. Pattern Anal. Machine Intell., vol. 11, no. 11, pp. 1203-1212, 1989.
[24] J. J. Scott, "A chess-playing program," inMachine Intelligence 4, B. Melzer and D. Michie, Eds. Edinburgh, Scotland: Edinburgh Univ. Press, 1969, pp. 255-265.
[25] A. K. Sen and A. Bagchi, "Fast recursive formulation for best-first search that allow controlled use of memory," inProc. 11th Int. Joint Conf. on Artificial Intell., 1989, pp. 297-302.
[26] D. J. Slate and L. R. Atkin, "Chess 4.5--The Northwestern University chess program," inChess Skill in Man and Machine, P. W. Frey, Ed. New York: Springer-Verlag, 1977, pp. 82-118.
[27] M. E. Stickel and W. M. Tyson, "An analysis of consecutively bounded depth-first search with applications in automated deduction," inProc. 9th Int. Joint Conf. on Artificial Intell., 1985, pp. 1073-75.
[28] G. C. Stockman, "A minimax algorithm better than alpha-beta?,"Artificial Intell., vol. 12, no. 2, pp. 179-196, 1979.
[29] B. W. Wah, "MIDA*: An IDA* search with dynamic control," Tech. Rep. UILU-ENG-91-2216, CRHC-91-9, Univ. of Illinois, Champaign, IL, 1991.
[30] A. L. Zobrist, "A new hashing method with applications for game playing," Tech. Rep. 88, Univ. of Wisconsin, Madison, WI, 1970. Reprinted inInt. Comput. Chess Assoc. J., vol. 13, no. 2, pp. 69-73, 1990.

Index Terms:
computational complexity; search problems; game theory; iterative methods; iterative-deepening search; breadth-first node expansion; depth-first searches; successively extended search horizons; space complexity; best-first searches; A* search; search efficiency; information management techniques; two-player games; fast-execution memory functions
Citation:
A. Reinefeld, T.A. Marsland, "Enhanced Iterative-Deepening Search," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, no. 7, pp. 701-710, July 1994, doi:10.1109/34.297950
Usage of this product signifies your acceptance of the Terms of Use.