Paper Info
Title
A formal description specification for multi-resolution modeling (MRM) based on DEVS formalism
Abstract
Multi-Resolution Modeling (MRM) is a relatively new research area. With the development of distributed interactive simulation, especially as the emergence of HLA, multi-resolution modeling becomes one of the key technologies for advanced modeling and simulation. There is little research in the area of the theory of multi-resolution modeling, especially the formal description of MRM. In this paper, we present a new concept for the description of multi-resolution modeling, named multi-resolution model family (MF). A multi-resolution model family is defined as the set of different resolution models of the same entity. The description of MF includes two parts: models of different resolution and their relations. Based on this new concept and DEVS formalism, we present a new multi-resolution model system specification, named MRMS (Multi-Resolution Model system Specification). And we present and prove some important properties of MRMS, especially the closure of MRMS under coupling operation. MRMS provides a foundation and a powerful description tool for the research of MRM. Using this description, we can further study the theory and implementation of MRM.
Year
DOI
Venue
2004
null
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Keywords
Field
DocType
formal description specification,multi-resolution modeling,new multi-resolution model system,formal description,new research area,devs formalism,new concept,advanced modeling,multi-resolution model system,different resolution model,powerful description tool,multi-resolution model family
Programming language,Computer science,Modeling and simulation,Model system,Distributed Interactive Simulation,Formal description,Theoretical computer science,DEVS,Formalism (philosophy),Management science
Conference
Volume
Issue
ISSN
3397
null
null
ISBN
Citations 
PageRank 
3-540-24476-X
4
0.48
References 
Authors
2
2
Name
Order
Citations
PageRank
Liu Baohong140.48
Kedi Huang27911.95