Improving Heuristics Through Relaxed Search - An Analysis of TP4 and HSP in the 2004 Planning Competition
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Description
The hm admissible heuristics for (sequential and temporal) regression planning are defined by a parameterized relaxation of the optimal cost function in the regression search space, where the parameter m offers a trade-off between the accuracy and computational cost of the heuristic. Existing methods for computing the hm heuristic require time exponential in m, limiting them to small values (m ≤ 2). The hm heuristic can also be viewed as the optimal cost function in a relaxation of the search...[Show more]
Collections | ANU Research Publications |
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Date published: | 2006 |
Type: | Journal article |
URI: | http://hdl.handle.net/1885/27325 |
Source: | Journal of Artificial Intelligence Research |
DOI: | 10.1613/jair.1885 |
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01_Haslum_Improving_Heuristics_Through_2006.pdf | 434.01 kB | Adobe PDF | Request a copy |
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