Abstract
The idea of bidirectional search has fascinated researchers for years: large gains seem intuitively possible because of the exponential growth of search trees. Furthermore, some researchers report significant gains for bidirectional search strategies. This is all the more frustrating for those practitioners that have failed to realize the promised improvements.
We suggest a model for perimeter search performance that, instead of simply counting nodes, counts the execution of important algorithmic subtasks and weights them with their runtime. We then use this model to predict total runtimes of perimeter search algorithms more accurately. Our model conforms to the observation that unidirectional search (IDA*) is a special case of its bidirectional counterpart, perimeter search (BIDA*), with a perimeter depth of 0. Using this insight, we can determine the optimal perimeter depth for BIDA* a priori, thus allowing BIDA* to subsume IDA*.
Our model forecasts that applications with expensive heuristic functions have little if anything to gain from perimeter search. Unfortunately, expensive heuristics are often used by high-performance programs. Our experiments show that on the 15-puzzle perimeter search narrowly outperforms its unidirectional counterpart. This finding is consistent with the literature and our model. However, it does not appear that a state-of-the-art implementation of a 15-puzzle solver can benefit from the perimeter search strategy.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
de Champeaux, D., Sint, L.: An improved bidirectional heuristic search algorithm. Journal of the Association for Computing Machinery 24, 177–191 (1977)
Kaindl, H., Kainz, G.: Bidirectional heuristic search reconsidered. Journal of Artificial Intelligence Research 7, 283–317 (1997)
de Champeaux, D.: Bidirectional heuristic search again. Journal of the Association for Computing Machinery 30, 22–32 (1983)
Pohl, I.: Bi-directional and heuristic search in path problems. Stanford University (1969), SLAC Report 104
Kwa, J.: BS*: An admissible bidirectional staged heuristic search algorithm. Artificial Intelligence 38, 95–109 (1989)
Hart, P., Nilsson, N., Raphael, B.: A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics 4, 100–107 (1968)
Hart, P., Nilsson, N., Raphael, B.: Correction to a formed basis for the heuristic determination of minimum cost paths. SIGART Newsletter 37, 9 (1972)
Dillenburg, J., Nelson, P.: Perimeter search. Artificial Intelligence 65, 165–178 (1994)
Manzini, G.: BIDA*: An improved perimeter search algorithm. Artificial Intelligence 75, 347–360 (1995)
Korf, R.: Depth-first iterative-deepening: An optimal admissible tree search. Artificial Intelligence 27, 97–109 (1985)
Korf, R., Reid, M.: Complexity analysis of admissible heuristic search. In: Fifteenth National Conference of the American Association for Artificial Intelligence (AAAI 1998), pp. 305–310. AAAI Press, Menlo Park (1998)
Korf, R., Reid, M., Edelkamp, S.: Time complexity of iterative-deepening-A*. Artificial Intelligence 129, 199–218 (2001)
Junghanns, A.: Pushing the Limits: New Developments in Single-Agent Search. PhD thesis, University of Alberta (1999)
Pearl, J.: Heuristics – Intelligent Search Strategies for Computer Problem Solving. Addison-Wesley Publishing Co., Reading (1984)
Linares, C.: Caracterización de los modelos de búsqueda de un agente con descripciones generalizadas de los nodos origen y destino. PhD thesis, Facultad de Informática. Universidad Politécnica de Madrid (2001)
Edelkamp, S., Korf, R.: The branching factor of regular search spaces. In: Fifteenth National Conference of the American Association for Artificial Intelligence (AAAI 1998), pp. 299–304. AAAI Press, Menlo Park (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
López, C.L., Junghanns, A. (2003). Perimeter Search Performance. In: Schaeffer, J., Müller, M., Björnsson, Y. (eds) Computers and Games. CG 2002. Lecture Notes in Computer Science, vol 2883. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-40031-8_23
Download citation
DOI: https://doi.org/10.1007/978-3-540-40031-8_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20545-6
Online ISBN: 978-3-540-40031-8
eBook Packages: Springer Book Archive