Business ecosystem modelling: Combining natural ecosystems and multi-agent systemsCitation formats

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Business ecosystem modelling: Combining natural ecosystems and multi-agent systems : Combining Natural Ecosystems and Multi-Agent Systems. / Marín, César A.; Stalker, Iain; Mehandjiev, Nikolay.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.. Vol. 4676 Springer Nature, 2007. p. 181-185.

Research output: Chapter in Book/Report/Conference proceedingChapter

Harvard

Marín, CA, Stalker, I & Mehandjiev, N 2007, Business ecosystem modelling: Combining natural ecosystems and multi-agent systems: Combining Natural Ecosystems and Multi-Agent Systems. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.. vol. 4676, Springer Nature, pp. 181-185, 11th International Workshop on Cooperative Information Agents, CIA 2007, Delft, 1/07/07.

APA

Marín, C. A., Stalker, I., & Mehandjiev, N. (2007). Business ecosystem modelling: Combining natural ecosystems and multi-agent systems: Combining Natural Ecosystems and Multi-Agent Systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci. (Vol. 4676, pp. 181-185). Springer Nature.

Vancouver

Marín CA, Stalker I, Mehandjiev N. Business ecosystem modelling: Combining natural ecosystems and multi-agent systems: Combining Natural Ecosystems and Multi-Agent Systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.. Vol. 4676. Springer Nature. 2007. p. 181-185

Author

Marín, César A. ; Stalker, Iain ; Mehandjiev, Nikolay. / Business ecosystem modelling: Combining natural ecosystems and multi-agent systems : Combining Natural Ecosystems and Multi-Agent Systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.. Vol. 4676 Springer Nature, 2007. pp. 181-185

Bibtex

@inbook{722f83069d814482b5dba28af7575098,
title = "Business ecosystem modelling: Combining natural ecosystems and multi-agent systems: Combining Natural Ecosystems and Multi-Agent Systems",
abstract = "The increasing popularity of the {"}business ecosystem{"} concept in (business) strategy reflects that it is seen as one way to cope with increasingly dynamic and complex business environments. Nevertheless, the lack of a convincing model of a business ecosystem has led to the development of software which only give organisations a partial aid whilst neglecting their need for adaptation. Research in Multi-Agent Systems has proved to be suitable for modelling interactions among disparate sort of entities such as organisations. On the other hand, natural ecosystems continue to adapt themselves to changes in their dynamic and complex environments. In this paper, we present the Dynamic Agent-based Ecosystem Model. It combines ideas from natural ecosystems and multi-agent systems for business interactions. {\circledC} Springer-Verlag Berlin Heidelberg 2007.",
author = "Mar{\'i}n, {C{\'e}sar A.} and Iain Stalker and Nikolay Mehandjiev",
year = "2007",
language = "English",
volume = "4676",
pages = "181--185",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.",
publisher = "Springer Nature",
address = "United States",

}

RIS

TY - CHAP

T1 - Business ecosystem modelling: Combining natural ecosystems and multi-agent systems

T2 - Combining Natural Ecosystems and Multi-Agent Systems

AU - Marín, César A.

AU - Stalker, Iain

AU - Mehandjiev, Nikolay

PY - 2007

Y1 - 2007

N2 - The increasing popularity of the "business ecosystem" concept in (business) strategy reflects that it is seen as one way to cope with increasingly dynamic and complex business environments. Nevertheless, the lack of a convincing model of a business ecosystem has led to the development of software which only give organisations a partial aid whilst neglecting their need for adaptation. Research in Multi-Agent Systems has proved to be suitable for modelling interactions among disparate sort of entities such as organisations. On the other hand, natural ecosystems continue to adapt themselves to changes in their dynamic and complex environments. In this paper, we present the Dynamic Agent-based Ecosystem Model. It combines ideas from natural ecosystems and multi-agent systems for business interactions. © Springer-Verlag Berlin Heidelberg 2007.

AB - The increasing popularity of the "business ecosystem" concept in (business) strategy reflects that it is seen as one way to cope with increasingly dynamic and complex business environments. Nevertheless, the lack of a convincing model of a business ecosystem has led to the development of software which only give organisations a partial aid whilst neglecting their need for adaptation. Research in Multi-Agent Systems has proved to be suitable for modelling interactions among disparate sort of entities such as organisations. On the other hand, natural ecosystems continue to adapt themselves to changes in their dynamic and complex environments. In this paper, we present the Dynamic Agent-based Ecosystem Model. It combines ideas from natural ecosystems and multi-agent systems for business interactions. © Springer-Verlag Berlin Heidelberg 2007.

M3 - Chapter

VL - 4676

SP - 181

EP - 185

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.

PB - Springer Nature

ER -