
Decision Making in Complex Systems
by Sokolova, Marina V.; Fernandez-Caballero, Antonio-
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Summary
Table of Contents
Decision making in Complex Systems | p. 1 |
Introduction | p. 1 |
Modeling of Natural and Complex Phenomena | p. 2 |
Complex Systems: Definition and Principal Characteristics | p. 2 |
Decision Making and Decision Support Systems | p. 5 |
Decision Making | p. 5 |
The Evolution of Decision Support Systems | p. 6 |
Decision Making in Complex Systems | p. 9 |
Composite Decisions | p. 11 |
Motivation | p. 13 |
Frameworks for the Design of Decision Support Systems | p. 13 |
The Need for an Interdisciplinary Approach | p. 14 |
Multi-agent Paradigm for Complex Systems Modeling | p. 15 |
A Review on Frameworks for Decision Support Systems | p. 19 |
Introduction | p. 19 |
Decision Support Systems in Academy and Research | p. 20 |
Agent-Based Frameworks for Decision Support Systems | p. 28 |
Frameworks for Multi-agent Systems Planning | p. 28 |
Software Tools for Multi-agent Systems Design and Implementation | p. 36 |
Comparison of Agent-Based Frameworks | p. 43 |
Design and Implementation of the DeciMaS Framework | p. 47 |
Introduction | p. 47 |
The DeciMaS Framework | p. 48 |
Approach towards Ontology Creation | p. 48 |
The General Structure of the System | p. 50 |
Description of the Ontological Basis of the Multi-agent Architecture | p. 54 |
The Domain of Interest Ontology | p. 55 |
The MAS Architecture Ontology | p. 55 |
The Tasks Ontology | p. 57 |
The Agent Ontology | p. 57 |
The Interactions Ontology | p. 58 |
The Distributed Meta-Ontology | p. 59 |
Data Mining Methods in the DeciMaS Framework | p. 60 |
Methods for Information Fusion and Preprocessing | p. 63 |
Methods for Knowledge Discovery | p. 68 |
Methods for Decision Generation | p. 86 |
A Case Study for the DeciMaS Framework | p. 89 |
Introduction | p. 89 |
Human Health Environmental Impact Assessment | p. 90 |
Environment and Human Health | p. 90 |
Environment Impact Assessment | p. 92 |
Design of the Agent-Based Decision Support System | p. 92 |
Meta-ontology of the System | p. 92 |
Logical Levels of the ADSS | p. 98 |
The Principal Abstractions of the System | p. 100 |
Implementation in Jack | p. 121 |
Program Architecture | p. 121 |
Defining Agents in Jack | p. 122 |
Data and Results | p. 139 |
Introduction | p. 139 |
Data for Experiment | p. 140 |
Data Retrieval and Fusion | p. 142 |
Information Fusion and Preprocessing | p. 144 |
Detection and Elimination of Artifacts | p. 144 |
Filling of Missing Values | p. 145 |
Smoothing Results | p. 146 |
Normalization Results | p. 147 |
Results of the Correlation Analysis | p. 147 |
Decomposition Results | p. 148 |
Knowledge Discovery Results | p. 150 |
Regression Models | p. 150 |
Neural Network Models | p. 152 |
Models Obtained with the Group Method of Data Handling | p. 155 |
Committee Machines | p. 157 |
Environmental Impact Assessment Results | p. 159 |
Decision Making | p. 161 |
Discussion of the Experiment | p. 165 |
Conclusions | p. 169 |
Conclusions | p. 169 |
Future Work | p. 171 |
References | p. 173 |
Table of Contents provided by Ingram. All Rights Reserved. |
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