Intelligent Systems Reference Library

The DeciMaS Agent-based Interdisciplinary Framework Approach

By: Marina V. Sokolova, Antonio FernÃ¡ndez Caballero

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Hardcover | 13 January 2012

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202 Pages

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24.13 x 16.51 x 1.91

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The study of complex systems attracts the attention of many researchers in diverse fields. Complex systems are characterized by a high number of entities and a high degree of interactions. One of the most important features is that they do not involve a central organizing authority, but the various elements that make up the systems are self-organized. Moreover, some complex systems possess an emergency priority: climate change and sustainable development research, studies of public health, ecosystem habitats, epidemiology, and medicine, among others.

Unfortunately, a great number of today's overlapping approaches fail to meet the needs of decision makers when managing complex domains. Indeed, the design of complex systems often requires the integration of a number of artificial intelligence tools and techniques. The problem can be viewed in terms of goals, states, and actions, choosing the best action to move the system toward its desired state or behavior. This is why agent-based approaches are used to model complex systems.

The main objective of this book is to bring together existing methods for decision support systems creation within a coherent agent-based framework and to provide an interdisciplinary and flexible methodology for modeling complex and systemic domains.

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You Can Find This Book In

Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Business & Management Management & Management Techniques Management Decision Making Engineering & Technology Technology in General Engineering in General

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Published: 22nd February 2014

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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.

Intelligent Systems Reference Library

The DeciMaS Agent-based Interdisciplinary Framework Approach

At a Glance

Hardcover

Shipping

How to return your order

Defective items

You Can Find This Book In

Other Editions and Formats

Paperback

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