Authors:
Rabia Aziza
1
;
Amel Borgi
1
;
Hayfa Zgaya
2
and
Benjamin Guinhouya
2
Affiliations:
1
LIPAH research laboratory and Université de Tunis El Manar, Tunisia
;
2
EA 2994, Public Health: Epidemiology and Healthcare Quality and University Lille, France
Keyword(s):
Complex Systems, Simulation, Agents, Constructivist Approach.
Related
Ontology
Subjects/Areas/Topics:
Agent Models and Architectures
;
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bioinformatics
;
Biomedical Engineering
;
Computational Intelligence
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Informatics in Control, Automation and Robotics
;
Information Systems Analysis and Specification
;
Intelligent Control Systems and Optimization
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Multi-Agent Systems
;
Operational Research
;
Simulation
;
Soft Computing
;
Software Engineering
;
Symbolic Systems
Abstract:
Complexity science offers many theories such as chaos theory and coevolutionary theory. These theories illustrate a large set of real life systems and help decipher their nonlinear and unpredictable behaviours. Categorizing an observed Complex System among these theories depends on the aspect that we intend to study, and it can help better understand the phenomena that occur within the system. This article aims to give an overview on Complex Systems and their modelling. Therefore, we compare these theories based on their main behavioural characteristics, e.g. emergence, adaptability, and dynamism. Then we compare the methods used in the literature to model and simulate Complex Systems, and we propose and discuss simple guidelines to help understand one’s Complex System and choose the most adequate model to simulate it.