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In the global information society, innovation is a highly pervasive
process that influences all facets of human life: cultural,
economic, political, and institutional. A desire to comprehend the
impacts of innovative change on so many areas of urban life
prompted the research project that has resulted in the publication
of this volume. Our research confirms that we are presently in the
midst of an era of rapid and explosive change. The primary engine
driving this latest transformation of the post-industrial society
is generally thought to be technological. But such an explanation
is too narrow. Broadly speaking, the age in which we find ourselves
could be more aptly described as a global, knowledge-intensive age.
Many of today's knowledge-intensive activities, like research and
development (R&D) programs, are being conducted with relative
ease on a multinational scale. As well as science having an
increasing impact on processes of innovation, R&D activities
also have become more complex. We can observe a growing
sophistication of learning-by-doing among creative economic agents.
This more sophisticated era of global knowledge exchange is
facilitated by major advances in our infrastructure networks. In
this highly interactive world, many innovations are by-products of
collective exchanges between cities far apart, simplified by the
ease of transport and communication. Thus, there is a need for us
to look more closely at various collective sequences of learning,
knowledge exchange and innovation in a spatial setting. This is the
primary purpose of this book.
Covering a broad range of topics, this text provides a
comprehensive survey of the modeling of chaotic dynamics and
complexity in the natural and social sciences. Its attention to
models in both the physical and social sciences and the detailed
philosophical approach make this a unique text in the midst of many
current books on chaos and complexity. Including an extensive index
and bibliography along with numerous examples and simplified
models, this is an ideal course text.
In the global information society, innovation is a highly pervasive
process that influences all facets of human life: cultural,
economic, political, and institutional. A desire to comprehend the
impacts of innovative change on so many areas of urban life
prompted the research project that has resulted in the publication
of this volume. Our research confirms that we are presently in the
midst of an era of rapid and explosive change. The primary engine
driving this latest transformation of the post-industrial society
is generally thought to be technological. But such an explanation
is too narrow. Broadly speaking, the age in which we find ourselves
could be more aptly described as a global, knowledge-intensive age.
Many of today's knowledge-intensive activities, like research and
development (R&D) programs, are being conducted with relative
ease on a multinational scale. As well as science having an
increasing impact on processes of innovation, R&D activities
also have become more complex. We can observe a growing
sophistication of learning-by-doing among creative economic agents.
This more sophisticated era of global knowledge exchange is
facilitated by major advances in our infrastructure networks. In
this highly interactive world, many innovations are by-products of
collective exchanges between cities far apart, simplified by the
ease of transport and communication. Thus, there is a need for us
to look more closely at various collective sequences of learning,
knowledge exchange and innovation in a spatial setting. This is the
primary purpose of this book.
Covering a broad range of topics, this text provides a
comprehensive survey of the modelling of chaotic dynamics and
complexity in the natural and social sciences. Its attention to
models in both the physical and social sciences and the detailed
philosophical approach make this an unique text in the midst of
many current books on chaos and complexity. Part 1 deals with the
mathematical model as an instrument of investigation. The general
meaning of modelling and, more specifically, questions concerning
linear modelling are discussed. Part 2 deals with the theme of
chaos and the origin of chaotic dynamics. Part 3 deals with the
theme of complexity: a property of the systems and of their models
which is intermediate between stability and chaos. Including an
extensive index and bibliography along with numerous examples and
simplified models, this is an ideal course text.
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