Chris Rayner, Nathan Sturtevant, and Michael Bowling. Subset Selection of Search Heuristics. In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI), pp. 637–643, 2013.
Constructing a strong heuristic function is a central problem in heuristic search. A common approach is to combine a number of heuristics by maximizing over the values from each. If a limit is placed on this number, then a subset selection problem arises. We treat this as an optimization problem, and proceed by translating a natural loss function into a submodular and monotonic utility function under which greedy selection is guaranteed to be near-optimal. We then extend this approach with a sampling scheme that retains provable optimality. Our empirical results show large improvements over existing methods, and give new insight into building heuristics for directed domains.
@InProceedings(13ijcai-hsubset, Title = "Subset Selection of Search Heuristics", Author = "Chris Rayner and Nathan Sturtevant and Michael Bowling", Booktitle = "Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI)", Pages = "637--643", Year = "2013", AcceptRate = "28\%", AcceptNumbers = "413 of 1473" )