{"type":"ScholarlyArticle","title":"Subset Selection of Search Heuristics","authors":[{"name":"D. Chris Rayner","slug":"d-chris-rayner","given":"D. Chris","family":"Rayner","affiliation":""},{"name":"Nathan R. Sturtevant","slug":"nathan-r-sturtevant","given":"Nathan R.","family":"Sturtevant","affiliation":""},{"name":"Michael H. Bowling","slug":"michael-h-bowling","given":"Michael H.","family":"Bowling","affiliation":""}],"abstract":"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.","doi":null,"url":"https://ijcai.org/proceedings/2013/101","pdf":"https://ijcai.org/proceedings/2013/0101.pdf","markdown":"https://ijcai.org/proceedings/2013/101.md","bibtex":"https://ijcai.org/proceedings/2013/bibtex/101","volume":{"slug":"2013","title":"Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2013","url":"https://ijcai.org/proceedings/2013/","year":2013,"location":"Beijing, China","dates":"3–9 August 2013","editors":"Francesca Rossi","isbn":"978-1-57735-633-2","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":101,"pages":{"first":637,"last":642},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}