000 03116nam a22005055i 4500
001 978-3-642-32952-4
003 DE-He213
005 20140220082854.0
007 cr nn 008mamaa
008 121116s2013 gw | s |||| 0|eng d
020 _a9783642329524
_9978-3-642-32952-4
024 7 _a10.1007/978-3-642-32952-4
_2doi
050 4 _aQA76.9.M35
072 7 _aGPFC
_2bicssc
072 7 _aTEC000000
_2bisacsh
082 0 4 _a620
_223
100 1 _aLizier, Joseph T.
_eauthor.
245 1 4 _aThe Local Information Dynamics of Distributed Computation in Complex Systems
_h[electronic resource] /
_cby Joseph T. Lizier.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2013.
300 _aXXIII, 235 p. 42 illus., 14 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 _aSpringer Theses, Recognizing Outstanding Ph.D. Research,
_x2190-5053
505 0 _aIntroduction -- Computation in complex systems -- Information storage -- Information transfer -- Information modifications -- Information dynamics in networks and phase transitions -- Coherent information structure in complex computation -- Information transfer in biological and bio-inspired systems -- Conclusion.
520 _aThe nature of distributed computation in complex systems has often been described in terms of memory, communication and processing. This thesis presents a complete information-theoretic framework to quantify these operations on information (i.e. information storage, transfer and modification), and in particular their dynamics in space and time. The framework is applied to cellular automata, and delivers important insights into the fundamental nature of distributed computation and the dynamics of complex systems (e.g. that gliders are dominant information transfer agents). Applications to several important network models, including random Boolean networks, suggest that the capability for information storage and coherent transfer are maximized near the critical regime in certain order-chaos phase transitions. Further applications to study and design information structure in the contexts of computational neuroscience and guided self-organization underline the practical utility of the techniques presented here.  
650 0 _aEngineering.
650 0 _aCoding theory.
650 0 _aArtificial intelligence.
650 0 _aBioinformatics.
650 0 _aPhysics.
650 1 4 _aEngineering.
650 2 4 _aComplexity.
650 2 4 _aCoding and Information Theory.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aComputational Biology/Bioinformatics.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642329517
830 0 _aSpringer Theses, Recognizing Outstanding Ph.D. Research,
_x2190-5053
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-32952-4
912 _aZDB-2-ENG
999 _c97306
_d97306