ACM Home Page
Please provide us with feedback. Feedback
From exponential to almost linear decomposability of finite or infinite trees
Full text PdfPdf (412 KB)
Source
Symposium on Applied Computing archive
Proceedings of the 2009 ACM symposium on Applied Computing table of contents
Honolulu, Hawaii
SESSION: Computational intelligence and image analysis track table of contents
Pages 897-902  
Year of Publication: 2009
ISBN:978-1-60558-166-8
Author
Khalil Djelloul  Université d'Orléans
Sponsor
SIGAPP: ACM Special Interest Group on Applied Computing
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 14,   Downloads (12 Months): 41,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1529282.1529478
What is a DOI?

ABSTRACT

First-order constraints are first-order formulas built on a set of function and relation symbols using the following logical symbols: =, true, false, ¬, ∧, ∨, →, ↔, ∀, ∃, (,). Over the last decade, first-order constraints have been efficiently used in the artificial intelligence world to model many kinds of complex problems such as: scheduling, resource allocation, configuration, temporal and spatial reasoning, computer graphics, bio-informatics. While theory of finite or infinite trees T has played a fundamental role for both modeling and solving these problems, the complexity of solving first-order constraints with nested quantifiers and negations in T has been proved to be inherently huge (a tower of powers of two). However, a new property called decomposability has been recently introduced and used as a black-box to build many efficient first-order constraint solvers over T. We show in this paper that the algorithm which is used in this black-box (i.e. the algorithm which performs decomposability) has an exponential time and space complexity. We then present a much more efficient algorithm in the form of four rewriting rules which can perform the same decomposability in an almost-linear time and space complexity.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
3
 
4
Colmerauer, A. Equations and inequations on finite and infinite trees. Proceeding of the International conference on the fifth generation of computer systems, pp. 8599. 1984.
 
5
Colmerauer, A., Kanoui, H. and Van-caneghem, M. Prolog, Theoretical Basis and Current Developments. TSI 2(4): 271311. 1983.
 
6
Colmerauer, A. Prolog and infinite trees. In K. L. Clark and S-A. Tarnlund, editors, Logic Programming. Academic Press. pp. 231251. 1982.
 
7
 
8
9
10
 
11
Duck, J., Stuckey, J., Garcya de la Banda., and C. Holzbaur. The refined operational semantics of Constraint Handling Rules. In proc ICLP'04 International Conference on Logic Programming, volume 3132 of LNCS, pages 90104. Springer, 2004.
12
 
13
Fruehwirth, T. Theory and Practice of Constraint Handling Rules. Special Issue on Constraint Logic Programming. Journal of Logic Programming. 37(13): 95--138. 1998.
 
14
 
15
Maher M. Complete Axiomatizations of the Algebras of Finite, Rational and Infinite Trees. In proc of LICS'88 IEEE Symposium on Logic in Computer Science. pp. 348--357. 1988.
16
17
 
18
 
19
20
 
21