A Simulation of Strategic Bargainings within a Biotechnology Cluster

2007 ◽  
pp. 335-351
Author(s):  
A. Berro ◽  
I. leroux
Keyword(s):  
Local Government ◽  
Simulation Model ◽  
Complex Adaptive Systems ◽  
Artificial Life ◽  
Adaptive Systems ◽  
Local Authorities ◽  
Local Coordination ◽  
Key Players ◽  
Complex Adaptive ◽  
End Use

This chapter introduces artificial life as a means of exploring strategic relations dynamics between firms and local authorities within a local biotechnology cluster. It argues that artificial life, combined with a conception of bioclusters as complex adaptive systems, offers a significant approach to understanding the co-evolution of strategies and the potential vulnerability of such systems. The simulation model involves firms and local government administrations that negotiate to share a quasi-rent, and which, to this end, use strategies that are to a greater or lesser extent sophisticated or opportunistic. The results show that the firms adjust their bargaining strategies according to their assessment of gains which might be collectively generated. The results also bring to light that the local authorities play a regulatory role against opportunism and that they are the key players in local coordination. Stemming from these simulations, the authors develop promising new avenues of theoretical and empirical research.

Simulation model of supply networks development

2019 ◽  
Author(s):  
Petr Fiala ◽  
Martina Kuncová
Keyword(s):  
Simulation Model ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Initial Conditions ◽  
Fitness Function ◽  
Network Systems ◽  
Network Growth ◽  
Fitness Value ◽  
Complex Adaptive ◽  
Fixed Structure

The paper is dedicated to network development in the network economy. The current economy needs to look not only at networks with only dynamic flows and with a fixed structure, but as a dynamic system its structure evolves and changes. Structure and behaviour dynamics of network systems can be modelled as complex adaptive systems and use agent-oriented simulation to demonstrate origin, perturbation effects, and sensitivity with regard to initial conditions. Survival of firms is associated with the value of so-called fitness function. Firms whose fitness value falls below a certain threshold will be extinguished. In this way, it is possible to partially model network growth. A simulation model in SIMUL8 is proposed.

Natural Language From Artificial Life

2002 ◽  
Vol 8 (2) ◽  
pp. 185-215 ◽  
Author(s):  
Simon Kirby
Keyword(s):  
Complex Adaptive Systems ◽  
Artificial Life ◽  
Adaptive Systems ◽  
Computational Simulation ◽  
Biological Evolution ◽  
Explanatory Theory ◽  
Fertile Ground ◽  
Complex Adaptive ◽  
Systems Learning ◽  
Theory Of Language

This article aims to show that linguistics, in particular the study of the lexico-syntactic aspects of language, provides fertile ground for artificial life modeling. A survey of the models that have been developed over the last decade and a half is presented to demonstrate that ALife techniques have a lot to offer an explanatory theory of language. It is argued that this is because much of the structure of language is determined by the interaction of three complex adaptive systems: learning, culture, and biological evolution. Computational simulation, informed by theoretical linguistics, is an appropriate response to the challenge of explaining real linguistic data in terms of the processes that underpin human language.

scholarly journals Picture This: The State of the Art in Visualization for Complex Adaptive Systems

2006 ◽  
Vol 12 (2) ◽  
pp. 189-192 ◽  
Author(s):  
Seth Bullock ◽  
Tom Smith ◽  
Jon Bird
Keyword(s):  
Complex Adaptive Systems ◽  
Artificial Life ◽  
Adaptive Systems ◽  
State Of The Art ◽  
Special Role ◽  
Special Issue ◽  
Future Developments ◽  
Complex Adaptive ◽  
High Level ◽  
Visualization Techniques

Visualization has an increasingly important role to play in scientific research. Moreover, visualization has a special role to play within artificial life as a result of the informal status of its key explananda: life and complexity. Both are poorly defined but apparently identifiable via raw inspection. Here we concentrate on how visualization techniques might allow us to move beyond this situation by facilitating increased understanding of the relationships between an ALife system's (low-level) composition and organization and its (high-level) behavior. We briefly review the use of visualization within artificial life, and point to some future developments represented by the articles collected within this special issue.

Conclusion: scaling down?

2016 ◽  
Author(s):  
Catherine Needham ◽  
Kerry Allen ◽  
Kelly Hall
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Social Care ◽  
Welfare System ◽  
Enterprise Development ◽  
Local Authorities ◽  
Care Services ◽  
Complex Adaptive ◽  
The Impact ◽  
Micro Enterprises

The concluding chapter considers the implications of the findings for the future of English social care services and for the broader health and welfare system. It suggests that local care economies are complex adaptive systems in which niche organisations like micro-enterprises can thrive but in which local authorities have weak coordinating tools to support micro-enterprise development. The employment of designated micro-enterprise coordinators within local authorities can enhance support for micro-enterprises, but even in localities with coordinators the micro-enterprises remain fragile. The chapter also considers whether the benefits of ‘smallness’ can be achieved through other means than micro-enterprises, discussing what can be learned from examples of large organisations which have found ways to nest smaller units within them. These discussions suggest opportunities for further research, particularly longitudinal and comparative research which stretch the impact of our findings beyond the timescale and geographical reach of our current study.

EMERGENT FEATURES IN A GENERAL FOOD WEB SIMULATION: LOTKA–VOLTERRA, GAUSE'S LAW, AND THE PARADOX OF ENRICHMENT

2013 ◽  
Vol 16 (08) ◽  
pp. 1350014 ◽  
Author(s):  
TED CARMICHAEL ◽  
MIRSAD HADZIKADIC
Keyword(s):  
Simulation Model ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Marine Ecosystem ◽  
System Level ◽  
Computer Simulation Model ◽  
Agent Based ◽  
Predator Prey ◽  
Paradox Of Enrichment ◽  
Complex Adaptive

Computer simulations of complex food-webs are important tools for deepening our understanding of these systems. Yet most computer models assume, rather than generate, key system-level patterns, or use mathematical modeling approaches that make it difficult to fully account for nonlinear dynamics. In this paper, we present a computer simulation model that addresses these concerns by focusing on assumptions of agent attributes rather than agent outcomes. Our model utilizes the techniques of complex adaptive systems and agent-based modeling so that system level patterns of a marine ecosystem emerge from the interactions of thousands of individual computer agents. This methodology is validated by using this general simulation model to replicate fundamental properties of a marine ecosystem, including: (i) the predator–prey oscillations found in Lotka–Volterra; (ii) the stepped pattern of biomass accrual from resource enrichment; (iii) the Paradox of Enrichment; and (iv) Gause's Law.

Artificial Life Down Under

2005 ◽  
Vol 11 (3) ◽  
pp. 397-399
Author(s):  
Hussein A. Abbass
Keyword(s):  
Complex Adaptive Systems ◽  
Artificial Life ◽  
Adaptive Systems ◽  
Complex Adaptive

For many years, Australian researchers have been contributing to the areas of artificial life and complex adaptive systems. This report highlights some of the Australian-based activities in these areas.

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