Dynamic Problem Solving in the Semantic Grid

SEMANTICS-ASSISTED PROBLEM SOLVING ON THE SEMANTIC GRID

Computational Intelligence ◽

10.1111/j.0824-7935.2005.00269.x ◽

2005 ◽

Vol 21 (2) ◽

pp. 157-176 ◽

Cited By ~ 22

Author(s):

Liming Chen ◽

Nigel Richard Shadbolt ◽

Feng Tao ◽

Carole Goble ◽

Colin Puleston ◽

...

Keyword(s):

Problem Solving ◽

Semantic Grid

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Knowledge Logistics as an Intelligent Service for Healthcare

Methods of Information in Medicine ◽

10.1055/s-0038-1633959 ◽

2005 ◽

Vol 44 (02) ◽

pp. 262-264 ◽

Cited By ~ 2

Author(s):

M. Pashkin ◽

N. Chilov ◽

T. Levashova ◽

A. Krizhanovsky ◽

A. Smirnov

Keyword(s):

Problem Solving ◽

Feasible Solution ◽

Complex Problem ◽

Complex Problem Solving ◽

Semantic Grid ◽

Constraint Networks ◽

Logic Module ◽

Time Minimization ◽

Insufficient Knowledge

Summary Objectives: The technology of grid services is developing fast. This paper presents an approach to the implementation of an intelligent grid service that configures a hospital taking advantage of the knowledge logistics idea. Methods: The presented approach is based on synergistic integration of knowledge acquired from distributed sources in order to obtain new or complement insufficient knowledge. Presented approach uses ontologies and the formalism of object-oriented constraint networks for knowledge representation and applies ILOG to constraint-based problem solving. Results: The application of the approach is illustrated via a decision support system for a fictitious case study of a hospital configuration in the Binni region. The system showed the ability to produce interrelated solutions for subtasks of the hospital configuration task based on the built ontology and input parameters. Besides, such preferences as cost or time minimization are also considered by the implemented fuzzy logic module that finds a feasible solution. Conclusions: KL would benefit from the grid, and particularly from the concept of a semantic grid. The scalable architecture of the approach enables its extension with regard to knowledge/information sources number and, thereby, with regard to factors taken into account during complex problem solving. Utilizing ontologies allows integration of the approach into existing processes and facilitates knowledge sharing with similar systems. Application of constraint networks allows rapid problem manipulation and usage of such existing efficient technologies as ILOG.

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