Dual phase evolution — a mechanism for self-organization in complex systems

2010 ◽  
pp. 58-65 ◽  
Author(s):  
David G. Green ◽  
Tania G. Leishman ◽  
Suzanne Sadedin
Keyword(s):  
Complex Systems ◽  
Phase Evolution ◽  
Self Organization ◽  
Dual Phase

COMPLEX BIOLOGICAL IMMUNE SYSTEM THROUGH THE EYES OF DUAL-PHASE EVOLUTION

2018 ◽  
Vol 26 (03) ◽  
pp. 473-493 ◽  
Author(s):  
SNEHAL B. SHINDE ◽  
MANISH P. KURHEKAR
Keyword(s):  
Phase Transitions ◽  
Immune System ◽  
Complex Adaptive Systems ◽  
Network Theory ◽  
Adaptive Systems ◽  
System Analysis ◽  
Phase Evolution ◽  
Self Organization ◽  
Dual Phase ◽  
Growth State

Dual-phase evolution (DPE) and the network theory help to analyze prominent properties of the complex adaptive systems (CASs) such as emergence and self-organization that are caused due to the phase transitions. These transitions are observed because of the increase and decrease in the number of system components and their interactions. The immune system, which is one of the CASs, provides an adaptive response to the foreign molecules. Prior to this response, the immune system is present in the circulation state and during the response, it moves into the growth state, where the number of immune cells and their cell–cell contacts increase rapidly. The phase transitions from the circulation state to the growth state and then back to the circulation state cause the emergence and self-organization of the immune system, respectively. There is a need to understand these complex cellular dynamics during the immune response. In this paper, we have proposed an integrated model of DPE, network theory, and the immune system that has helped to understand and analyze the phases and properties of the immune system. Analysis of the growth phase network is provided and it is concluded that this network exhibits scale-free nature following power law for the degree distribution of nodes.

In-Between and Through: Architecture and Complexity

2005 ◽  
Vol 3 (3) ◽  
pp. 335-354 ◽  
Author(s):  
Clarissa Ribeiro Pereira de Almeida ◽  
Anja Pratschke ◽  
Renata La Rocca
Keyword(s):  
Complex System ◽  
Software Engineering ◽  
Complex Systems ◽  
Design Process ◽  
Three Dimensional ◽  
Self Organization ◽  
Three Dimensional Modeling ◽  
Dimensional Modeling ◽  
Complex Thought ◽  
Basic Characteristics

This paper draws on current research on complexity and design process in architecture and offers a proposal for how architects might bring complex thought to bear on the understanding of design process as a complex system, to understand architecture as a way of organizing events, and of organizing interaction. Our intention is to explore the hypothesis that the basic characteristics of complex systems – emergence, nonlinearity, self-organization, hologramaticity, and so forth – can function as effective tools for conceptualization that can usefully extend the understanding of the way architects think and act throughout the design process. To illustrate the discussions, we show how architects might bring complex thought inside a transdisciplinary design process by using models such as software engineering diagrams, and three-dimensional modeling network environments such as media to integrate, connect and ‘trans–act’.

scholarly journals SELF-ORGANIZATION IN COMPLEX SYSTEMS AS DECISION MAKING

2014 ◽  
Vol 17 (03n04) ◽  
pp. 1450016 ◽  
Author(s):  
V. I. YUKALOV ◽  
D. SORNETTE
Keyword(s):  
Decision Making ◽  
Complex Systems ◽  
Mathematical Formulation ◽  
Conditional Entropy ◽  
Self Organization ◽  
Entropy Maximization ◽  
Natural Systems ◽  
Macroscopic States ◽  
System States ◽  
Statistical Systems

The idea is advanced that self-organization in complex systems can be treated as decision making (as it is performed by humans) and, vice versa, decision making is nothing but a kind of self-organization in the decision maker nervous systems. A mathematical formulation is suggested based on the definition of probabilities of system states, whose particular cases characterize the probabilities of structures, patterns, scenarios, or prospects. In this general framework, it is shown that the mathematical structures of self-organization and of decision making are identical. This makes it clear how self-organization can be seen as an endogenous decision making process and, reciprocally, decision making occurs via an endogenous self-organization. The approach is illustrated by phase transitions in large statistical systems, crossovers in small statistical systems, evolutions and revolutions in social and biological systems, structural self-organization in dynamical systems, and by the probabilistic formulation of classical and behavioral decision theories. In all these cases, self-organization is described as the process of evaluating the probabilities of macroscopic states or prospects in the search for a state with the largest probability. The general way of deriving the probability measure for classical systems is the principle of minimal information, that is, the conditional entropy maximization under given constraints. Behavioral biases of decision makers can be characterized in the same way as analogous to quantum fluctuations in natural systems.

A Dual Phase Evolution Model of Adaptive Radiation in Landscapes

2007 ◽  
pp. 131-143 ◽  
Author(s):  
Greg Paperin ◽  
David Green ◽  
Suzanne Sadedin ◽  
Tania Leishman
Keyword(s):  
Adaptive Radiation ◽  
Phase Evolution ◽  
Evolution Model ◽  
Dual Phase

scholarly journals Emergence and Self-Organisation of Complex Systems: the role of energy flows and information a philosophical approach

2018 ◽  
Vol 2 (1) ◽  
pp. 31 ◽  
Author(s):  
Norbert Fenzl
Keyword(s):  
Complex Systems ◽  
Driving Forces ◽  
Open Systems ◽  
Structural Information ◽  
Self Organization ◽  
Specific Information ◽  
Philosophical Approach ◽  
Energy Flows ◽  
Energy And Material Flows

How order emerges from noise? How higher complexity arises from lower complexity? For what reason a certain number of open systems start interacting in a coherent way, producing new structures, building up cohesion and new structural boundaries? To answer these questions we need to precise the concepts we use to describe open and complex systems and the basic driving forces of self-organization.   We assume that self-organization processes are related to the flow and throughput of Energy and Matter and the production of system-specific Information. These two processes are intimately linked together: Energy and Material flows are the fundamental carriers of signs, which are processed by the internal structure of the system to produce system-specific structural Information (Is). So far, the present theoretical reflections are focused on the emergence of open systems and on the role of Energy Flows and Information in a self-organizing process. Based on the assumption that Energy, Mass and Information are intrinsically linked together and are fundamental aspects of the Universe, we discuss how they might be related to each other and how they are able to produce the emergence of new structures and systems. 

Self-Organization in Multiplex Networks

2018 ◽  
pp. 148-158
Author(s):  
Nikos E. Kouvaris ◽  
Albert Díaz-Guilera
Keyword(s):  
Complex Systems ◽  
Network Structure ◽  
Reaction Diffusion ◽  
Reaction Diffusion Equations ◽  
Diffusion Equations ◽  
Self Organization ◽  
Multiplex Networks ◽  
The Way

The chapter “Self-Organization in Multiplex Networks” discusses the use of multiplex networks in studying complex systems and synchronization. An important question in the research of complex systems concerns the way the network structure shapes the hosted dynamics and leads to a plethora of self-organization phenomena. Complex systems consist of nodes having some intrinsic dynamics, usually nonlinear, and are connected through the links of the network. Such systems can be studied by means of discrete reaction–diffusion equations; reaction terms account for the dynamics in the nodes, whereas diffusion terms describe the coupling between them. This chapter discusses how multiplex networks are suitable for studying such systems by providing two illustrative examples of self-organization phenomena occurring in them.

Additive Noise Tunes the Self-Organization in Complex Systems

Synergetics ◽  
2020 ◽  
pp. 183-195
Author(s):  
Axel Hutt ◽  
Jérémie Lefebvre
Keyword(s):  
Complex Systems ◽  
Additive Noise ◽  
The Self ◽  
Self Organization
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