000 03617nam a22005175i 4500
001 978-3-642-11692-6
003 DE-He213
005 20140220084531.0
007 cr nn 008mamaa
008 100517s2010 gw | s |||| 0|eng d
020 _a9783642116926
_9978-3-642-11692-6
024 7 _a10.1007/978-3-642-11692-6
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aLevi, Paul.
_eauthor.
245 1 0 _aSymbiotic Multi-Robot Organisms
_h[electronic resource] :
_bReliability, Adaptability, Evolution /
_cby Paul Levi, Serge Kernbach.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2010.
300 _a480p. 104 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 _aCognitive Systems Monographs,
_x1867-4925 ;
_v7
505 0 _aConcepts of Symbiotic Robot Organisms -- Heterogeneous Multi-Robot Systems -- Cognitive Approach in Artificial Organisms -- Adaptive Control Mechanisms -- Learning, Artificial Evolution and Cultural Aspects of Symbiotic Robotics -- Final Conclusions.
520 _aThis book is devoted to the study of the evolution of self-organised multicellular structures and the remarkable transition from unicellular to multicellular life. Multicellular organisms provide the inspiration for the development of novel principles of adaptation and evolution for robotics and, in particular, for so-called multi-robot organisms. Multi-robot organisms are defined as large-scale swarms of robots that can physically dock with each other and symbiotically share energy and computational resources within a single "artificial-life-form". When it is advantageous to do so, these robots can dynamically aggregate and self-assemble into one or many symbiotic organisms in order to collectively interact with the physical world via a variety of sensors and actuators. Bio-inspired evolutionary paradigms, combined with robot embodiment and swarm-emergent phenomena, enable the organisms to autonomously manage their own hardware and software organisation. In this way, artificial robotic organisms become self-configuring from both hardware and software perspectives. This could lead to not only extremely adaptive, evolve-able and scalable robotic systems, but robot organisms also able to reprogram themselves without human supervision and new, previously unforeseen, functionality to emerge. This book introduces new concepts for symbiotic robot organisms and reports on experience of researching and developing such systems. In the long term it is intended to apply this experience in the construction and maintenance of real-world technical systems based on these concepts.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aPhysics.
650 0 _aControl engineering systems.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aControl , Robotics, Mechatronics.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aStatistical Physics, Dynamical Systems and Complexity.
650 2 4 _aComplexity.
700 1 _aKernbach, Serge.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642116919
830 0 _aCognitive Systems Monographs,
_x1867-4925 ;
_v7
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-11692-6
912 _aZDB-2-ENG
999 _c111912
_d111912