A multiobjective frontier search algorithm

Authors:
L. Mandow;J. L. Pérez De la Cruz
Affiliations:
Dpto. Lenguajes y Ciencias de la Computación, Universidad de Málaga, Málaga, Spain;Dpto. Lenguajes y Ciencias de la Computación, Universidad de Málaga, Málaga, Spain
Venue:
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Year:
2007

Citing 8
Cited 3

Depth-first iterative-deepening: an optimal admissible tree search

Artificial Intelligence
Multiobjective A*

Journal of the ACM (JACM)
Linear-space best-first search

Artificial Intelligence
Iterative deepening multiobjective A*

Information Processing Letters
State Space Search with Prioritised Soft Constraints

Applied Intelligence
Multiobjective heuristic state-space planning

Artificial Intelligence
Frontier search

Journal of the ACM (JACM)
A new approach to multiobjective A* search

IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence

Frontier Search for Bicriterion Shortest Path Problems

Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
A memory-efficient search strategy for multiobjective shortest path problems

KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
Anytime algorithms for biobjective heuristic search

AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

The paper analyzes the extension of frontier search to the multiobjective framework. A frontier multiobjective A* search algorithm is developed, some formal properties are presented, and its performance is compared to those of other multiobjective search algorithms. The new algorithm is adequate for both monotone and non-monotone heuristics.