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001			103281
003			DE-He213
005			20240111050146.0
007			cr nn 008mamaa
008			150515s2015 gw | s |||| 0|eng d
020			_a9783319168234
024	7		_a10.1007/978-3-319-16823-4 _2doi
050		4	_aQ342 _b.J664 2015 EB
040			_aES-MaUEC _bspa
100	1		_aJones, Jeff _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _0http://id.loc.gov/authorities/names/n97123862 _1http://viaf.org/viaf/17424387/ _1http://dbpedia.org/resource/Jeff_Jones_(cricketer)
245	1	0	_aFrom Pattern Formation to Material Computation _bMulti-agent Modelling of Physarum Polycephalum _cby Jeff Jones.
264		1	_aCham _bSpringer International Publishing _c2015
300			_a1 recurso en línea (XVI, 370 páginas 209 ilustraciones, 145 ilustraciones a color.)
490	0		_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	3		_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		7	_aSistemas multiagente _2embne _9667894
650		7	_aInteligencia artificial _2embne _9413115
776	0	8	_iEdición impresa: _z9783319168241
776	0	8	_iEdición impresa: _z9783319168227
776	0	8	_iEdición impresa: _z9783319386515
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-16823-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
490	0		_aEngineering (Springer-11647)
998			_b03/2019 _dz _ef _feng _ggw _h0
999			_c103281 _d103281 _x1