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From pattern formation to material c...

Jones, Jeff.

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From pattern formation to material computation = multi-agent modelling of physarum polycephalum /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	From pattern formation to material computation/ by Jeff Jones.
其他題名:	multi-agent modelling of physarum polycephalum /
作者:	Jones, Jeff.
出版者:	Cham :Springer International Publishing : : 2015.,
面頁冊數:	xvi, 370 p. :ill., digital ;24 cm.
內容註:	Part 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.
Contained By:	Springer eBooks
標題:	Multiagent systems. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-16823-4
ISBN:	9783319168234 (electronic bk.)

From pattern formation to material computation = multi-agent modelling of physarum polycephalum /
Jones, Jeff.

From pattern formation to material computationmulti-agent modelling of physarum polycephalum /[electronic resource] :by Jeff Jones. - Cham :Springer International Publishing :2015. - xvi, 370 p. :ill., digital ;24 cm. - Emergence, complexity and computation,v.152194-7287 ;. - Emergence, complexity and computation ;v.5..

Part 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.

This 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.

ISBN: 9783319168234 (electronic bk.)

Standard No.: 10.1007/978-3-319-16823-4doiSubjects--Topical Terms:

1048048
Multiagent systems.

LC Class. No.: Q342

Dewey Class. No.: 006.3

From pattern formation to material computation = multi-agent modelling of physarum polycephalum /
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505 0 $a Part 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 $a This 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.
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