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Recent approaches to goal and plan recognition using classical planningdomains have achieved state of the art results in terms of both recognitiontime and accuracy by using heuristics based on planning landmarks. To achievesuch fast recognition time these approaches use efficient, but incomplete,algorithms to extract only a subset of landmarks for planning domains andproblems, at the cost of some accuracy. In this paper, we investigate theimpact and effect of using various landmark extraction algorithms capable ofextracting a larger proportion of the landmarks for each given planningproblem, up to exhaustive landmark extraction. We perform an extensiveempirical evaluation of various landmark-based heuristics when using differentpercentages of the full set of landmarks. Results show that having morelandmarks does not necessarily mean achieving higher accuracy and lower spread,as the additional extracted landmarks may not necessarily increase be helpfultowards the goal recognition task.

The More the Merrier?! Evaluating the Effect of Landmark Extraction Algorithms on Landmark-Based Goal Recognition