Weighted heuristic search in networks

The evaluation function used in heuristic search algorithms commonly has the form , where n is any node in the network, is the cost of the best path currently known from the start node to n, and is the heuristic estimate associated with node n. A more general form of the evaluation function can be obtained by incorporating a weighting parameter α:

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, where 0≤ α ≤1. Such an evaluation function has been used in some recent experimental investigations of the 8-puzzle problem. In this paper a theoretical framework is developed for the analysis of the worst-case behavior of weighted heuristic search algorithms. A new algorithm is proposed whose worst-case performance characteristics are greatly superior to those of earlier algorithms in terms of the following two measures: how good is the solution, and how many nodes are expanded. Bounds are also obtained on some useful network parameters for both general and special types of heuristic estimate functions.