Is it possible to "guide" the process of self-organisation
towards specific patterns and outcomes?Wouldn t this be
self-contradictory?After all, a self-organising process assumes a
transition into a more organised form, or towards a more structured
functionality, in the "absence" of centralised control.Then how can
we place the guiding elements so that they do not override rich
choices potentially discoverable by an uncontrolled process?
This book presents different approaches to resolving this
"paradox."In doing so, the presented studies address a broad range
of phenomena, ranging from autopoietic systems to morphological
computation, and from small-world networks to information cascades
in swarms.A large variety of methods is employed, from spontaneous
symmetry breaking to information dynamics to evolutionary
algorithms, creating a rich spectrum reflecting this emerging
field.
Demonstrating several foundational theories and frameworks, as
well as innovative practical implementations, "Guided
Self-Organisation: Inception," will be an invaluable tool for
advanced students and researchers in a multiplicity of fields
across computer science, physics and biology, including information
theory, robotics, dynamical systems, graph theory, artificial life,
multi-agent systems, theory of computation and machine
learning.
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