000 04283nam a22005535i 4500
001 978-3-319-16823-4
003 DE-He213
005 20200420220216.0
007 cr nn 008mamaa
008 150515s2015 gw | s |||| 0|eng d
020 _a9783319168234
_9978-3-319-16823-4
024 7 _a10.1007/978-3-319-16823-4
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aJones, Jeff.
_eauthor.
245 1 0 _aFrom Pattern Formation to Material Computation
_h[electronic resource] :
_bMulti-agent Modelling of Physarum Polycephalum /
_cby Jeff Jones.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aXVI, 370 p. 209 illus., 145 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 ;
_v15
505 0 _aPart I Slime Mould Physarum polycephalum. Part II Modelling Physarum polycephalum. -- Part III Material Computation in a Multi-agent Model of Physarum polycephalum: Mechanisms and Applications -- Part IV From Emergent Oscillations to Collective Transport and Amoeboid Movement -- Part V Conclusions and Beyond Physarum models.
520 _aThis book addresses topics of mobile multi-agent systems, pattern formation, biological modelling, artificial life, unconventional computation, and robotics. The behaviour of a simple organism which is capable of remarkable biological and computational feats that seem to transcend its simple component parts is examined and modelled. In this book the following question is asked: How can something as simple as Physarum polycephalum - a giant amoeboid single-celled organism which does not possess any neural tissue, fixed skeleton or organised musculature - can approximate complex computational behaviour during its foraging, growth and adaptation of its amorphous body plan, and with such limited resources? To answer this question the same apparent limitations as faced by the organism are applied: using only simple components with local interactions. A synthesis approach is adopted and a mobile multi-agent system with very simple individual behaviours is employed. It is shown their interactions yield emergent behaviour showing complex self-organised pattern formation with material-like evolution. The presented model reproduces the biological behaviour of Physarum; the formation, growth and minimisation of transport networks. In its conclusion the book moves beyond Physarum and provides results of scoping experiments approximating other complex systems using the multi-agent approach. The results of this book demonstrate the power and range of harnessing emergent phenomena arising in simple multi-agent systems for biological modelling, computation and soft-robotics applications. It methodically describes the necessary components and their interactions, showing how deceptively simple components can create powerful mechanisms, aided by abundant illustrations, supplementary recordings and interactive models. It will be of interest to those in biological sciences, physics, computer science and robotics who wish to understand how simple components can result in complex and useful behaviours and who wish explore the potential of guided pattern formation themselves.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aBioinformatics.
650 0 _aComputational intelligence.
650 0 _aComplexity, Computational.
650 0 _aRobotics.
650 0 _aAutomation.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aRobotics and Automation.
650 2 4 _aComplexity.
650 2 4 _aBioinformatics.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319168227
830 0 _aEmergence, Complexity and Computation,
_x2194-7287 ;
_v15
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-16823-4
912 _aZDB-2-ENG
942 _cEBK
999 _c51627
_d51627