{"type":"ScholarlyArticle","title":"Towards Finding Optimal Solutions with Non-Admissible Heuristics: A New Technique","authors":[{"name":"Henry W. Davis","slug":"henry-w-davis","given":"Henry W.","family":"Davis","affiliation":"Department of Computer Science Wright State University , Dayton Ohio 45435"},{"name":"Anna Bramanti-Gregor","slug":"anna-bramanti-gregor","given":"Anna","family":"Bramanti-Gregor","affiliation":"Department of Computer Science Wright State University , Dayton Ohio 45435"},{"name":"Xiaoteng Chen","slug":"xiaoteng-chen","given":"Xiaoteng","family":"Chen","affiliation":"Department of Computer Science Wright State University , Dayton Ohio 45435"}],"abstract":"A problem with A* is that it fails to guarantee optimal solutions when its heuristic, h, overestimates. Since optimal solutions are often desired and an underestimating h is not always available, we seek to remedy this. From a nonadmissible h an admissible one is generated using h 's statistical properties. The new heuristic, hm, is obtained by inverting h with respect to its own least upper bound function. The set of nodes expanded when A* uses g + hm as an evaluator is compared with the set of nodes expanded using other approaches which have been suggested in the literature. A considerable potential savings in node expansion when using hm is indicated. In 8-puzzle experiments A* using g +hm expands one fifth as many nodes as does the best alternative approach.","doi":null,"url":"https://ijcai.org/proceedings/1989/48","pdf":"https://ijcai.org/proceedings/1989/0048.pdf","markdown":"https://ijcai.org/proceedings/1989/48.md","bibtex":"https://ijcai.org/proceedings/1989/bibtex/48","volume":{"slug":"1989","title":"Proceedings of the Eleventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1989","url":"https://ijcai.org/proceedings/1989/","year":1989,"location":"Detroit, Michigan, USA","dates":"August 20-25 1989","editors":"N. S. Sridharan","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Search","track":"Search","number":48,"pages":{"first":303,"last":307},"keywords":[],"videos":[],"references":[{"position":1,"raw":"[Bagchi and Mahanti, 1983] A. Bagchi and A. Mahanti, Search algorithms under different kinds of heuristics -A comparative study, JACM, 30(1):1-21, 1983.","title":"Search algorithms under different kinds of heuristics -A comparative study","authors":"A Bagchi, A Mahanti","year":"1983","venue":"JACM","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Bagchi and Mahanti, 1985] A. Bagchi and A. Mahanti, Three approaches to heuristic search in networks, JACM, 32(1):1-27, 1985.","title":"Three approaches to heuristic search in networks","authors":"A Bagchi, A Mahanti","year":"1985","venue":"JACM","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Chakrabarti et al., 1988] P. Chakrabarti, S. Chose, and S. C. DeSarkar, Admissibility of AO* when heuristics overestimate,Artificial Intelligence 34:97- 113, 1988.","title":"Admissibility of AO* when heuristics overestimate","authors":"P Chakrabarti, S Chose, S C Desarkar","year":"1988","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Dechter and Pearl, 1985] R. Dechter and J. Pearl, Generalized best-first strategy and the optimality of A*, JACM, 32(3):505-536, 1985.","title":"Generalized best-first strategy and the optimality of A","authors":"R Dechter, J Pearl","year":"1985","venue":"JACM","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Gashnig, 1979] J. G. Gaschnig, Performance Measure- ment and Analysis of Certain Search Algorithms, Ph.D Thesis, Carnegie-Mellon University, 1979.","title":"Performance Measurement and Analysis of Certain Search Algorithms","authors":"J G Gaschnig","year":"1979","venue":null,"doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Huyn et al., 1980] N. Huyn, R. Dechter and J. Pearl, Probabilistic analysis of complexity of A*, Artificial Intelligence 15:241-254, 1980.","title":"Probabilistic analysis of complexity of A","authors":"N Huyn, R Dechter, J Pearl","year":"1980","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Korf, 1985] R. E. Korf, Depth-first iterative deepening: an optimal admissible tree search, Artificial Intelligence, 25:97-109, 1985.","title":"Depth-first iterative deepening: an optimal admissible tree search","authors":"R E Korf","year":"1985","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Nilsson, 1980] N. J. Nilsson, Principle of Artificial Intelligence, Tioga Publishing Co., Palo Alto, Ca., 1980.","title":"Principle of Artificial Intelligence","authors":"N J Nilsson","year":"1980","venue":null,"doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Pearl, 1984] J. Pearl, Heuristics, Addison-Wesley, Reading, Mass., 1984.","title":"Heuristics","authors":"J Pearl","year":"1984","venue":null,"doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Politowski, 1986] G. Politowski, On the Construction of Heuristic Functions, Ph.D. Thesis, University of California, Santa Barbara, 1986.","title":"On the Construction of Heuristic Functions","authors":"G Politowski","year":"1986","venue":null,"doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}