A constraint decomposition method for spatio-temporal configuration problems

Authors:
Toshikazu Tanimoto
Affiliations:
Digital Equipment Corporation Japan, Tokyo, Japan
Venue:
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Year:
1993

Citing 13
Cited 0

The complexity of some polynomial network consistency algorithms for constraint satisfaction problems

Artificial Intelligence
Network-based heuristics for constraint-satisfaction problems

Artificial Intelligence
An incremental constraint solver

Communications of the ACM
The design and analysis of spatial data structures

The design and analysis of spatial data structures
VLSI cell placement techniques

ACM Computing Surveys (CSUR)
A dynamic algorithm for placing rectangles without overlapping

Journal of Information Processing
Temporal constraint networks

Artificial Intelligence - Special issue on knowledge representation
PictureEditorII: a conversational graphical editing system considering the degree of constraint

CG International '92 Proceedings of the 10th International Conference of the Computer Graphics Society on Visual computing : integrating computer graphics with computer vision: integrating computer graphics with computer vision
A geometric constraint engine

Artificial Intelligence - Special volume on constraint-based reasoning
Maintaining knowledge about temporal intervals

Communications of the ACM
Perspective of Constraint-Based Reasoning: An Introductory Tutorial

Perspective of Constraint-Based Reasoning: An Introductory Tutorial
Reasoning about Gradual Changes of Topological Relationships

Proceedings of the International Conference GIS - From Space to Territory: Theories and Methods of Spatio-Temporal Reasoning on Theories and Methods of Spatio-Temporal Reasoning in Geographic Space
Reasoning in time and space

IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes a flexible framework and an efficient algorithm for constraint-based spatio-temporal configuration problems. Binary constraints between spatio-temporal objects are first converted to constraint regions, which are then decomposed into hierarchical data structures; based on this constraint decomposition, an improved backtracking algorithm called HBT can compute a solution quite efficiently. In contrast to other approaches, the proposed method is characterized by the efficient handling of arbitrarily-shaped objects, and the flexible integration of quantitative and qualitative constraints; it allows a wide range of objects and constraints to be utilized for specifying a spatio-temporal configuration. The method is intended primarily for configuration problems in user interfaces, but can effectively be applied to similar problems in other areas as well.