On the Space-Time Trade-Off in Solving Constraint Satisfaction Problems

Abstract

A common technique for bounding the runtime required to solve a constraint satisfaction problem is to exploit the structure of the problem's constraint graph [Dechter, 92]. We show that a simple structure-based technique with a minimal space requirement, pseudo-tree search [Freuder & Quinn, 85], is capable of bounding runtime almost as effectively as the best exponential space-consuming schemes. Specifically, if we let n denote the number of variables in the problem, w * denote the exponent in the complexity function of the best structure-based techniques, and h denote the exponent from pseudotree search, we show h < {w * + 1) (lg(n) + 1). The result should allow reductions in the amount of real-time accessible memory required for predicting runtime when solving CSP equivalent problems. 1

Cite

Text

Jr. and Miranker. "On the Space-Time Trade-Off in Solving Constraint Satisfaction Problems." International Joint Conference on Artificial Intelligence, 1995.

Markdown

[Jr. and Miranker. "On the Space-Time Trade-Off in Solving Constraint Satisfaction Problems." International Joint Conference on Artificial Intelligence, 1995.](https://mlanthology.org/ijcai/1995/jr1995ijcai-space/)

BibTeX

@inproceedings{jr1995ijcai-space,
  title     = {{On the Space-Time Trade-Off in Solving Constraint Satisfaction Problems}},
  author    = {Jr., Roberto J. Bayardo and Miranker, Daniel P.},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {1995},
  pages     = {558-562},
  url       = {https://mlanthology.org/ijcai/1995/jr1995ijcai-space/}
}