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The complexity of issues requiring rational decision making grows
and thus such decisions are becoming more and more difficult,
despite advances in methodology and tools for decision support and
in other areas of research. Globalization, interlinks between
environmental, industrial, social and political issues, and rapid
speed of change all contribute to the increase of this complexity.
Specialized knowledge about decision-making processes and their
support is increasing, but a large spectrum of approaches presented
in the literature is typically illustrated only by simple examples.
Moreover, the integration of model-based decision support
methodologies and tools with specialized model-based knowledge
developed for handling real problems in environmental, engineering,
industrial, economical, social and political activities is often
not satisfactory. Therefore, there is a need to present the state
of art of methodology and tools for development of model-based
decision support systems, and illustrate this state by applications
to various complex real-world decision problems. The monograph
reports many years of experience of many researchers, who have not
only contributed to the developments in operations research but
also succeeded to integrate knowledge and craft of various
disciplines into several modern decision support systems which have
been applied to actual complex decision-making processes in various
fields of policy making. The experience presented in this book will
be of value to researchers and practitioners in various fields. The
issues discussed in this book gain in importance with the
development of the new era of the information society, where
information, knowledge, and ways of processing them become a
decisive part of human activities. The examples presented in this
book illustrate how how various methods and tools of model-based
decision support can actually be used for helping modern decision
makers that face complex problems. Overview of the contents: The
first part of this three-part book presents the methodological
background and characteristics of modern decision-making
environment, and the value of model-based decision support thus
addressing current challenges of decision support. It also provides
the methodology of building and analyzing mathematical models that
represent underlying physical and economic processes, and that are
useful for modern decision makers at various stages of decision
making. These methods support not only the analysis of
Pareto-efficient solutions that correspond best to decision maker
preferences but also allow the use of other modeling concepts like
soft constraints, soft simulation, or inverse simulation. The
second part describes various types of tools that are used for the
development of decision support systems. These include tools for
modeling, simulation, optimization, tools supporting choice and
user interfaces. The described tools are both standard,
commercially available, and nonstandard, public domain or shareware
software, which are robust enough to be used also for complex
applications. All four environmental applications (regional water
quality management, land use planning, cost-effective policies
aimed at improving the European air quality, energy planning with
environmental implications) presented in the third part of the book
rely on many years of cooperation between the authors of the book
with several IIASA's projects, and with many researchers from the
wide IIASA network of collaborating institutions. All these
applications are characterized by an intensive use of model-based
decision support. Finally, the appendix contains a short
description of some of the tools described in the book that are
available from IIASA, free of charge, for research and educational
purposes. The experiences reported in this book indicate that the
development of DSSs for strategic environmental decision making
should be a joint effort involving experts in the subject area,
modelers, and decision support experts. For the other experiences
discussed in this book, the authors stress the importance of good
data bases, and good libraries of tools. One of the most important
requirements is a modular structure of a DSS that enhances the
reusability of system modules. In such modular structures, user
interfaces play an important role. The book shows how modern
achievements in mathematical programming and computer sciences may
be exploited for supporting decision making, especially about
strategic environmental problems. It presents the methodological
background of various methods for model-based decision support and
reviews methods and tools for model development and analysis. The
methods and tools are amply illustrated with extensive
applications. Audience: This book will be of interest to
researchers and practitioners in the fields of model development
and analysis, model-based decision analysis and support,
(particularly in the environment, economics, agriculture,
engineering, and negotiations areas) and mathematical programming.
For understanding of some parts of the text a background in
mathematics and operational research is required but several
chapters of the book will be of value also for readers without such
a background. The monograph is also suitable for use as a text book
for courses on advanced (Master and Ph.D.) levels for programs on
Operations Research, decision analysis, decision support and
various environmental studies (depending on the program different
parts of the book may be emphasized).
"Creative Environments" is a follow-up on the book Creative
Space in the same series and by the same authors, serving this time
as editors of a broader book on computational intelligence and
knowledge engineering tools for supporting knowledge creation. This
book contains four parts. The first part presents a further
development of models of knowledge creation presented already in
Creative Space, in particular the Triple Helix of normal academic
knowledge creation and a new, integrated model of normal academic
and organizational knowledge creation, called Nanatsudaki (seven
waterfalls) Model. The second part presents computational
intelligence tools for knowledge acquisition by machine learning
and data mining, for debating, brainstorming, for roadmapping and
for integrated support of academic creativity. The third part
presents the use of statistics for creativity support, virtual
laboratories, gaming and role playing for creativity support,
methods of knowledge representation and multiple criteria
aggregation, distance and electronic learning. The last part
addresses knowledge management and philosophical issues and
contains chapters: on management of technology and knowledge
management for academic R and D; on knowledge management and
creative holism or systems thinking in the knowledge age; on
technology and change or the role of technology in knowledge
civilisation; on the emergence of complex concepts in science; and
the final chapter on summary and conclusions, including a proposal
of an integrated episteme of constructive evolutionary objectivism,
necessary for the knowledge civilization age.
Creative Space summarizes and integrates the various up-to-date
approaches of computational intelligence to knowledge and
technology creation including the specific novel feature of
utilizing the creative abilities of the human mind, such as tacit
knowledge, emotions and instincts, and intuition. It analyzes
several important approaches of this new paradigm such as the
Shinayakana Systems Approach, the organizational knowledge creation
theory, in particular SECI Spiral, and the Rational Theory of
Intuition - resulting in the concept of Creative Space. This
monograph presents and analyzes in detail this new concept together
with its ontology - the list and meanings of the analyzed nodes of
this space and of the character of transitions linking these
nodes.
"Creative Environments" is a follow-up on the book Creative
Space in the same series and by the same authors, serving this time
as editors of a broader book on computational intelligence and
knowledge engineering tools for supporting knowledge creation. This
book contains four parts. The first part presents a further
development of models of knowledge creation presented already in
Creative Space, in particular the Triple Helix of normal academic
knowledge creation and a new, integrated model of normal academic
and organizational knowledge creation, called Nanatsudaki (seven
waterfalls) Model. The second part presents computational
intelligence tools for knowledge acquisition by machine learning
and data mining, for debating, brainstorming, for roadmapping and
for integrated support of academic creativity. The third part
presents the use of statistics for creativity support, virtual
laboratories, gaming and role playing for creativity support,
methods of knowledge representation and multiple criteria
aggregation, distance and electronic learning. The last part
addresses knowledge management and philosophical issues and
contains chapters: on management of technology and knowledge
management for academic R and D; on knowledge management and
creative holism or systems thinking in the knowledge age; on
technology and change or the role of technology in knowledge
civilisation; on the emergence of complex concepts in science; and
the final chapter on summary and conclusions, including a proposal
of an integrated episteme of constructive evolutionary objectivism,
necessary for the knowledge civilization age.
Creative Space summarizes and integrates the various up-to-date
approaches of computational intelligence to knowledge and
technology creation including the specific novel feature of
utilizing the creative abilities of the human mind, such as tacit
knowledge, emotions and instincts, and intuition. It analyzes
several important approaches of this new paradigm such as the
Shinayakana Systems Approach, the organizational knowledge creation
theory, in particular SECI Spiral, and the Rational Theory of
Intuition - resulting in the concept of Creative Space. This
monograph presents and analyzes in detail this new concept together
with its ontology - the list and meanings of the analyzed nodes of
this space and of the character of transitions linking these
nodes.
The complexity of issues requiring rational decision making grows
and thus such decisions are becoming more and more difficult,
despite advances in methodology and tools for decision support and
in other areas of research. Globalization, interlinks between
environmental, industrial, social and political issues, and rapid
speed of change all contribute to the increase of this complexity.
Specialized knowledge about decision-making processes and their
support is increasing, but a large spectrum of approaches presented
in the literature is typically illustrated only by simple examples.
Moreover, the integration of model-based decision support
methodologies and tools with specialized model-based knowledge
developed for handling real problems in environmental, engineering,
industrial, economical, social and political activities is often
not satisfactory. Therefore, there is a need to present the state
of art of methodology and tools for development of model-based
decision support systems, and illustrate this state by applications
to various complex real-world decision problems. The monograph
reports many years of experience of many researchers, who have not
only contributed to the developments in operations research but
also succeeded to integrate knowledge and craft of various
disciplines into several modern decision support systems which have
been applied to actual complex decision-making processes in various
fields of policy making. The experience presented in this book will
be of value to researchers and practitioners in various fields. The
issues discussed in this book gain in importance with the
development of the new era of the information society, where
information, knowledge, and ways of processing them become a
decisive part of human activities. The examples presented in this
book illustrate how how various methods and tools of model-based
decision support can actually be used for helping modern decision
makers that face complex problems. Overview of the contents: The
first part of this three-part book presents the methodological
background and characteristics of modern decision-making
environment, and the value of model-based decision support thus
addressing current challenges of decision support. It also provides
the methodology of building and analyzing mathematical models that
represent underlying physical and economic processes, and that are
useful for modern decision makers at various stages of decision
making. These methods support not only the analysis of
Pareto-efficient solutions that correspond best to decision maker
preferences but also allow the use of other modeling concepts like
soft constraints, soft simulation, or inverse simulation. The
second part describes various types of tools that are used for the
development of decision support systems. These include tools for
modeling, simulation, optimization, tools supporting choice and
user interfaces. The described tools are both standard,
commercially available, and nonstandard, public domain or shareware
software, which are robust enough to be used also for complex
applications. All four environmental applications (regional water
quality management, land use planning, cost-effective policies
aimed at improving the European air quality, energy planning with
environmental implications) presented in the third part of the book
rely on many years of cooperation between the authors of the book
with several IIASA's projects, and with many researchers from the
wide IIASA network of collaborating institutions. All these
applications are characterized by an intensive use of model-based
decision support. Finally, the appendix contains a short
description of some of the tools described in the book that are
available from IIASA, free of charge, for research and educational
purposes. The experiences reported in this book indicate that the
development of DSSs for strategic environmental decision making
should be a joint effort involving experts in the subject area,
modelers, and decision support experts. For the other experiences
discussed in this book, the authors stress the importance of good
data bases, and good libraries of tools. One of the most important
requirements is a modular structure of a DSS that enhances the
reusability of system modules. In such modular structures, user
interfaces play an important role. The book shows how modern
achievements in mathematical programming and computer sciences may
be exploited for supporting decision making, especially about
strategic environmental problems. It presents the methodological
background of various methods for model-based decision support and
reviews methods and tools for model development and analysis. The
methods and tools are amply illustrated with extensive
applications. Audience: This book will be of interest to
researchers and practitioners in the fields of model development
and analysis, model-based decision analysis and support,
(particularly in the environment, economics, agriculture,
engineering, and negotiations areas) and mathematical programming.
For understanding of some parts of the text a background in
mathematics and operational research is required but several
chapters of the book will be of value also for readers without such
a background. The monograph is also suitable for use as a text book
for courses on advanced (Master and Ph.D.) levels for programs on
Operations Research, decision analysis, decision support and
various environmental studies (depending on the program different
parts of the book may be emphasized).
This book presents selected papers from an international workshop
devoted tothe theory, techniques and tools of decision analysis and
support. Major trends in the development of this field are
stressed, such as the tendency to place the final user of a
decision support system in the center of attention, or an emerging
connection between tools and software environments for modeling and
for decision support. The volume is acontinuation of the reports on
earlier meetings which were published in the same series.
It is not easy to summarize -even in a volume -the results of a
scientific study con ducted by circa 30 researchers, in four
different research institutions, though cooperating between them
and jointly with the International Institute for Applied Systems
Analysis, but working part-time, sponsored not only by IIASA's
national currency funds, but also by several other research grants
in Poland. The aims of this cooperative study were de fined broadly
by its title Theory, Software and Testing Examples for Decision
Support Systems. The focusing theme was the methodology of decision
analysis and support related to the principle of reference point
optimization (developed by the editors of this volume and called
also variously: aspiration-led decision support, quasi-satisfying
framework of rationality, DIDAS methodology etc. ). This focusing
theme motivated extensive theoretical research - from basic
methodological issues of decision analysis, through various results
in mathematical programming (in the fields of large scale and
stochastic optimization, nondifferentiable optimization,
cooperative game theory) mo tivated and needed because of this
theme, through methodological issues related to software
development to issues resulting from testing and applications. We
could not include in this volume all papers -theoretical,
methodological, appiied, software manu als and documentation
-written during this cooperative study."
These Proceedings report the scientific results of an International
Workshop on Large-Scale Modelling and Interactive Decision Analysis
organized Jointly by the System and Decision Sciences Program of
the International Institute for Applied Systems Analysis (IIASA,
located in Laxenburg, Austria), and the Institute for Informatics
of the Academy of Sciences of the GDR (located in Berlin, GDR). The
Workshop was held at a historically well-known place - the Wartburg
Castl- near Eisenach (GDR). (Here Martin Luther translated the
Bible into German.) More than fifty scientists representing
thirteen countries participated. This Workshop is one of a series
of meetings organizE d by or In collaboration with IIASA about
which two of the Lecture Notes In Economics and Mathematical
Systems have already reported (Voi. 229 and Vol. 246). This time
the aim of the meeting was to discuss methodological and practical
problems associated with the modelling of large-scale systems and
new approaches In interactive decision analysis based on advanced
information processing systems.
These Proceedings report the scientific results of the Summer Study
on Plural Rationality and Interactive Decision Processes orga nized
jointly by the System and Decision Sciences Program of the Inter
national Institute for Applied Systems Analysis (located in
Laxenburg, Austria) and the Hungarian Committee for Applied Systems
Analysis. The Study, which was held in Sopron over the period 16-26
Augus.t 1984, had a very special character. Sixty-eight researchers
from sixteen coun tr es participated, most of them contributing
papers or experiments. In addition many members of IIASA's Young
Scientists Summer Program were present. All of these participants
were heavily involved in dis cussions; discussions that were not
limited to the allotted time but extended well into the evenings
and nights. By design, the Study gathered specialists from many
disciplines, from philosophy and cultur al anthropology, through
decision theory, game theory and economics, to engineering and
applied mathematics. A further element of diversity was the
representation of several varieties of culture, from typically
Western countries, through Middle and Eastern Europe, to the Far
East."
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