000 03285nam a22005415i 4500
001 978-3-642-53734-9
003 DE-He213
005 20200421111852.0
007 cr nn 008mamaa
008 131219s2014 gw | s |||| 0|eng d
020 _a9783642537349
_9978-3-642-53734-9
024 7 _a10.1007/978-3-642-53734-9
_2doi
050 4 _aQA76.9.M35
072 7 _aGPFC
_2bicssc
072 7 _aTEC000000
_2bisacsh
082 0 4 _a620
_223
245 1 0 _aGuided Self-Organization: Inception
_h[electronic resource] /
_cedited by Mikhail Prokopenko.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2014.
300 _aXXII, 475 p. 172 illus., 54 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aEmergence, Complexity and Computation,
_x2194-7287 ;
_v9
505 0 _aFoundational frameworks -- Coordinated behaviour and learning within an embodied agent -- Swarms and networks of agents.
520 _aIs 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.
650 0 _aEngineering.
650 0 _aComputers.
650 0 _aArtificial intelligence.
650 0 _aStatistical physics.
650 0 _aComputational intelligence.
650 0 _aComplexity, Computational.
650 1 4 _aEngineering.
650 2 4 _aComplexity.
650 2 4 _aTheory of Computation.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aComputational Intelligence.
650 2 4 _aNonlinear Dynamics.
700 1 _aProkopenko, Mikhail.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642537332
830 0 _aEmergence, Complexity and Computation,
_x2194-7287 ;
_v9
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-53734-9
912 _aZDB-2-ENG
942 _cEBK
999 _c56142
_d56142