Issue No. 05 - May (1991 vol. 13)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.134045
<p>Parallel window search is applied to single-agent problems by having different processes simultaneously perform iteration of Iterative-Deepening-A* (IDA*) on the same problem but with different cost thresholds. This approach is limited by the time to perform the goal iteration. To overcome this disadvantage, the authors consider node ordering. They discuss how global node ordering by minimum h among nodes with equal f=g+h values can reduce the time complexity of serial IDA* by reducing the time to perform the iterations prior to the goal iteration. Finally, the two ideas of parallel window search and node ordering are combined to eliminate the weaknesses of each approach while retaining the strengths. The resulting approach, called simply parallel window search, can be used to find a near-optimal solution quickly, improve the solution until it is optimal, and then finally guarantee optimality, depending on the amount of time available.</p>
parallel window search; single-agent problems; Iterative-Deepening-A*; node ordering; time complexity; computational complexity; iterative methods; optimisation; parallel algorithms; search problems
C. Powley and R. Korf, "Single-Agent Parallel Window Search," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 13, no. , pp. 466-477, 1991.