Complex adaptive system theory,agent-based modeling,and simulation in dominant technology formation

Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.

Patterns of Interactions of the Complex City System:Emotional Urban Objects as Triggering Agents-A Secondary Publication

This article presents an analysis of the patterns of interactions resulting from the positive and negative emotional events that occur in cities,considering them as complex systems.It explores,from the imaginaries,how certain urban objects can act as emotional agents and how these events affect the urban system as a whole.An adaptive complex systems perspective is used to analyze these patterns.The results show patterns in the processes and dynamics that occur in cities based on the objects that affect the emotions of the people who live there.These patterns depend on the characteristics of the emotional charge of urban objects,but they can be generalized in the following process:(1)immediate reaction by some individuals;(2)emotions are generated at the individual level which begins to generalize,permuting to a collective emotion;(3)a process of reflection is detonated in some individuals from the reading of collective emotions;(4)integration/significance in the community both at the individual and collective level,on the concepts,roles and/or functions that give rise to the process in the system.Therefore,it is clear that emotions play a significant role in the development of cities and these aspects should be considered in the design strategies of all kinds of projects for the city.Future extensions of this work could include a deeper analysis of specific emotional events in urban environments,as well as possible implications for urban policy and decision making.

Robustness of critical points in a complex adaptive system： Effects of hedge behavior

In our recent papers, we have identified a class of phase transitions in the market-directed resource- allocation game, and found that there exists a critical point at which the phase transitions occur. The critical point is given by a certain resource ratio. Here, by performing computer simulations and theoretical analysis, we report that the critical point is robust against various kinds of human hedge behavior where the numbers of herds and contrarians can be varied widely. This means that the critical point can be independent of the total number of participants composed of normal agents, herds and contrarians, under some conditions. This finding means that the critical points we identified in this complex adaptive system （with adaptive agents） may also be an intensive quantity, similar to those revealed in traditional physical systems （with non-adaptive units）.

Theory and model of water resources complex adaptive allocation system

Complex adaptive sys tem theory is a new and important embranchment of system science, which prov ides a new thought to research water resources allocation system. Based on the a nalysis of complexity and complex adaptive mechanism of water resources allocat ion system, a fire-new analysis model is presented in this paper. With t he description of dynamical mechanism of system, behavior characters of agents and the evaluation method of system status, an integrity research system is built to analyse the evolvement rule of water resources allocation system. A nd a brief research for the impact of water resources allocation in benefi cial regions of the Water Transfer from South to North China Project is conducted.

A Method for Reducing Ocean Wave-Induced Magnetic Noises in Shallow-Water MT Data Using a Complex Adaptive Filter

In shallow-water areas,the marine magnetotelluric(MT)method faces a challenge in the investigation of seabed conductivity structures due to electrical and magnetic noises induced by ocean waves,which seriously contaminate MT data.Ocean waves can affect electric and magnetic fields to different extents.In general,their influence on magnetic fields is considerably greater than that on electric fields.In this paper,a complex adaptive filter is adopted to reduce wave-induced magnetic noises in the frequency domain.The processing results of synthetic and measured MT data indicate that the proposed method can effectively reduce wave-induced magnetic noises and provide reliable apparent resistivity and phase data.

Complex Systems Theory: Some Considerations for Sociology

This essay presents a reflection on the main implications of Complexity Theory for science in general, redefining and dispelling myths of traditional science, and Sociology in particular, suggesting a redefinition of Parsons’ classic concept of Social System, articulated around the property of self-maintenance of order rather than on its possible discontinuity and instability. It argues that Complexity Theory has established the limits of Classic Science, leading to a more realistic awareness of working and evolution mechanisms of Natural and Social Systems and showing the limits of our capacity to predict and control events. Dissipative structures have shown the creative role of time. Instability, emergence, surprise, unpredictability are the rule rather than the exception when systems move away from equilibrium (entropy), even if these processes are generated from a system’s deterministic working mechanisms. Therefore, we have come to realize how constructive the contribution of Complexity is, in regards to the long lasting problem of the relationship between order and disorder. Today, the terms of this relationship have been re-specified in its new configuration of inter-relationship link, according to a unicum which finds its synthesis in self-organization and deterministic chaos concepts. From this perspective, as Prigogine suggested, studies on Complex Systems are heading toward a historical, biological conception of Physics, and a new alliance between natural systems and living, social systems. Non-linearity, far from equilibrium self-organization, emergence and surprise meet at all levels, as this paper attempts to highlight. In Sociology, insights of Complexity Theory have contributed to a new way of thinking about social systems, by re-addressing some fundamental issues starting to social system, emergence and change concepts. The current social system conception as complex dynamical systems is supported by a profitable use of non-liner models (in particular, the Logistic map) in the study of social processes.

Modelling Immune System:Principles,Models,Analysis and Perspectives

The biological immune system is a complex adaptive system.There are lots of benefits for building the model of the immune system.For biological researchers,they can test some hypotheses about the infection process or simulate the responses of some drugs.For computer researchers,they can build distributed,robust and fault tolerant networks inspired by the functions of the immune system.This paper provides a comprehensive survey of the literatures on modelling the immune system.From the methodology perspective,the paper compares and analyzes the existing approaches and models,and also demonstrates the focusing research effort on the future immune models in the next few years.

Adaptive evolvement of information age C^4ISR structure

Command, control, communication, computing, intel- ligence, surveillance and reconnaissance （C^4ISR） in information age is a complex system whose structure always changes ac- tively or passively during the warfare. Therefore, it is important to optimize the structure, especially in ambiguous and quick-tempo modern warfare. This paper proposes an adaptive evolvement mechanism for the C^4ISR structure to survive the changeable warfare. Firstly, the information age C^4ISR structure is defined and modeled based on the complex network theory. Secondly, taking the observe, orient, decide and act （OODA） model into consideration, four kinds of loops in the C^4ISR structure are pro- posed and their coefficient of networked effects （CNE） is further defined. Then, the adaptive evolvement mechanisms of the four kinds of loops are presented respectively. Finally, taking the joint air-defense C^4ISR as an example, simulation experiments are im- plemented, which validate the evolvement mechanism and show that the information age C41SR structure has some characteristics of small-world network and scale-free network.

Theoretical convergence analysis of complex Gaussian kernel LMS algorithm

With the vigorous expansion of nonlinear adaptive filtering with real-valued kernel functions,its counterpart complex kernel adaptive filtering algorithms were also sequentially proposed to solve the complex-valued nonlinear problems arising in almost all real-world applications.This paper firstly presents two schemes of the complex Gaussian kernel-based adaptive filtering algorithms to illustrate their respective characteristics.Then the theoretical convergence behavior of the complex Gaussian kernel least mean square（LMS） algorithm is studied by using the fixed dictionary strategy.The simulation results demonstrate that the theoretical curves predicted by the derived analytical models consistently coincide with the Monte Carlo simulation results in both transient and steady-state stages for two introduced complex Gaussian kernel LMS algonthms using non-circular complex data.The analytical models are able to be regard as a theoretical tool evaluating ability and allow to compare with mean square error（MSE） performance among of complex kernel LMS（KLMS） methods according to the specified kernel bandwidth and the length of dictionary.

Globally Important Agricultural Heritage Systems(GIAHS)of China:the challenge of complexity in research

The challenge of researching Globally Important Agricultural Heritage Systems(GIAHS)as complex systems forms the subject matter of this study.Complex adaptive systems are those that combine natural ecological processes with human interactions to produce a mutually supportive agro-ecological system.In China,these highly varied systems have the added dimension of long historical time,in that they have evolved over many centuries and thus add a historical dimension to the natural and human dimensions of complexity.In preparing research on GIAHS,it is clear that seeing GIAHS sites as whole systems is an essential starting and ending point.Examining the adaptive capacity of a GIAHS with its multiple scales and complex interdependencies is a major challenge for researchers accustomed to specialized disciplinary thinking.A GIAHS represents a mature agro-ecological system with human agency as a central component that has been honed over many centuries,and has already adapted to many perturbations and changes.The beauty of the GIAHS is in the integration of custom,knowledge,and practice,and it should be studied for its"wholeness"as well as for its resilience and capacity for"self organization."The agro-ecological approach opens the possibility of researching a system as a whole and of taking its complexity seriously.This study reviews the essential features of the GIAHS as a complex adaptive system where uncertainty is normal and surprise is welcome and,in a case study of Qingtian rice–fish culture system,focuses on new perturbations,namely loss of young people and the introduction of tourism.

Desertification risk,economic resilience and social issues:From theory to practice

Land degradation and early forms of desertification in both advanced economies and emerging countries reflect complex socio-environmental processes driven by multiple interactions between biophysical and socioeconomic forces across different spatial scales.The present study investigates desertification risk,land degradation,and socio-demographic dynamics through the lens of“resilience,”adopting complex adaptive systems(CAS)thinking.The resilience of socio-environmental systems exposed to land degradation is defined as the capacity of a regional economy to respond to crises and reorganize by making changes to preserve functions,structure,and feedback,and to promote future development options.By reviewing the socioeconomic resilience of local socio-ecological systems exposed to land degradation,this study achieves a better comprehension of the multifaceted processes that lead to a higher risk of desertification and the intimate relationship with underlying population trends and demographic dynamics.A comprehensive approach based on resilience thinking was formulated to review both environmental and socio-demographic issues at the landscape scale,and provide a suitable foundation for sustainability science and regional development policies.

CAS-based Water Resources Optimal Allocation and Dynamic Simulation for Sewage Irrigation Area

Based on the theory of complex adaptive system(CAS),the optimal allocation model of water resources in sewage irrigation areas was established,which provided new ideas and application value for the rational utilization of agricultural production and waste water resources.The results demonstrated that the difference of crop energy capture mainly depended on the development stage.Waste water with a certain concentration was able to promote crop growth,while excessive concentration inhibited crop growth.The correlation between water absorption rate and leaf area index was close(R=0.9498,p<0.01).The amount of bad seeds increased at a speed of 34.7·d^-1,when system irrigated randomly in the seedling stage,while it tended to remain stable at a speed of 0.3·d^-1 after plants entering the mature stage which impacted the total yields of crops.

How Do Precision Medicine and System Biology Response to Human Body's Complex Adaptability？

In the field of life sciences, although system biology and ＂precision medicine＂ introduce some complex scientific methods and techniques, it is still based on the ＂analysis–reconstruction＂ of reductionist theory as a whole. Adaptability of complex system increase system behaviour uncertainty as well as the difficulties of precise identification and control. It also put systems biology research into trouble. To grasp the behaviour and characteristics of organism fundamentally, systems biology has to abandon the ＂analysis–reconstruction＂ concept. In accordance with the guidelines of complexity science, systems biology should build organism model from holistic level, just like the Chinese medicine did in dealing with human body and disease. When we study the living body from the holistic level, we will find the adaptability of complex system is not the obstacle that increases the difficulty of problem solving. It is the ＂exceptional＂, ＂right-hand man＂ that helping us to deal with the complexity of life more effectively.

Distributed Adaptive Synchronization of Complex Dynamical Network with Unknown Time-varying Weights

A new approach of adaptive distributed control is proposed for a class of networks with unknown time-varying coupling weights. The proposed approach ensures that the complex dynamical networks achieve asymptotical synchronization and all the closed-loop signals are bounded. Furthermore, the coupling matrix is not assumed to be symmetric or irreducible and asymptotical synchronization can be achieved even when the graph of network is not connected. Finally, a simulation example shows the feasibility and effectiveness of the approach.

Footholds optimization for legged robots walking on complex terrain

This paper proposes a novel continuous footholds optimization method for legged robots to expand their walking ability on complex terrains.The algorithm can efficiently run onboard and online by using terrain perception information to protect the robot against slipping or tripping on the edge of obstacles,and to improve its stability and safety when walking on complex terrain.By relying on the depth camera installed on the robot and obtaining the terrain heightmap,the algorithm converts the discrete grid heightmap into a continuous costmap.Then,it constructs an optimization function combined with the robot’s state information to select the next footholds and generate the motion trajectory to control the robot’s locomotion.Compared with most existing footholds selection algorithms that rely on discrete enumeration search,as far as we know,the proposed algorithm is the first to use a continuous optimization method.We successfully implemented the algorithm on a hexapod robot,and verified its feasibility in a walking experiment on a complex terrain.

Emergence in cyber-physical systems:potential and risk

Cyber-physical systems(CPSs)are distributed assemblages of computing,communicating,and physical components that sense their environment,algorithmically assess the incoming information,and affect their physical environment.Thus,they share a common structure with other complex adaptive systems,and therefore share both the possible benefits and the probable harmful effects of emergent phenomena.Emergence is an often unexpected pattern that arises from the interactions among the individual system components and the environment.In this paper we focus on three major problems concerning emergence in the context of CPSs:how to successfully exploit emergence,how to avoid its detrimental effects in a single CPS,and how to avoid harmful emergence that arises due to unexpected interaction among several independently developed CPSs that are operating in the same environment.We review the state of the research with regard to these problems and outline several approaches that could be used to address them.

The Dynamics of Interorganizational Collaboration in Disaster Management:A Network Study Based on Flood Disasters in China

Interorganizational collaboration networks have become an important tool for disaster management.However,research on how different organizations can effectively collaborate throughout the entire disaster management process in centralized states such as China is scarce.This study begins to fill this lacuna by investigating interorganizational collaboration in different phases of disaster management and analyzing changes in the structure of the networks constructed during the preparedness and response phases of the 2020 flood disaster in Hubei Province,China.Building on the complex adaptive systems(CAS)theory,we argue that interorganizational collaboration changes dynamically according to its tasks and requirements.In the preparedness phase,interorganizational collaborations primarily follow established plans and choose horizontal selforganized collaboration mechanisms.However,when the urgent information and resource requirements increase in the response phase,many organizations choose vertical mandatory collaboration mechanisms.We found that organizations at the central and provincial levels in China were well positioned to coordinate information and resources and strengthen the interorganizational collaboration and communication that is crucial in disaster management.These findings contribute to the study of interorganizational collaboration networks in disaster management.

Chaotic-periodic transition in a two-sided minority game

Phase transitions are being used increasingly to probe the collective behaviors of social human systems. In this study, we propose a different way of investigating such transitions in a human system by establishing a two-sided minority game model. A new type of agents who can actively transfer resources are added to our artificial bipartite resource-allocation market. The degree of deviation from equilibria is characterized by the entropy-like quantity of market complexity. Under different threshold values, Qth, two phases are found by calculating the exponents of the associated power spectra. For large values of Qth, the general motion of strategies for the agents is relatively periodic whereas for low values of Qth, the motion becomes chaotic. The transition occurs abruptly at a critical value of Qty. Our simulation results were also tested based on human experiments. The results of this study suggest that a chaotic-periodic transition related to the quantity of market information should exist in most bipartite markets, thereby allowing better control of such a transi- tion and providing a better understanding of the endogenous emergence of business cycles from the perspective of quantum mechanics.

Evolution of Specialization with Reachable Transaction Scope Based on a Simple and Symmetric Firm Resource Allocation Model

In the last decade, as an emerging transaction measure driven by computer and internet technology, e-commerce experienced explosive growth in many areas. It has greatly broken down the limitations of space and time to economic activities, thus changing the rules of business fundamentally. Significant work has been done to understand the laws of e-commerce from multiple dimensions, but the question of how e-commerce shapes firms＇ specialization and market structure from the perspective of spatial factors remains obscure. In this paper, we propose a simple and symmetric firm resource allocation model with a specialized-economy production function and market size constraint, to investigate how individual firms adjust resource allocation with reachable transaction scope expanded. It is shown that with the expansion of reachable transaction scope, individual firms discretely take back one unit resource from a low-investment direction and, instead, channel it to a ＂specialized direction＂. Meanwhile, at the macro level, an optimal division network evolves from a static self-sufficient stage to a diverse semi-specialized stage, and finally to a highly integrated completely specialized stage. Ergo, a Complex Adaptive System （CAS） based simulation framework is constructed. Designed simulation experiments are carried out and confirm to the analysis result of our proposed model.

Governance interactions of spatial data infrastructures: an agent-based modelling approach

In order to facilitate and coordinate spatial data sharing and exchange,many organisations have developed spatial data infrastructures(SDIs).SDI governance plays a pivotal role in the development and evolution of an SDI,but as SDIs are complex adaptive systems,governing is a challenge.This research therefore proposes a complexity perspective to SDI governance by exploring the use of agent-based modelling to simulate and examine SDI governance interactions.In this agent-based simulation,we examine interactions between SDI stakeholders,data availability and the effects of different governance styles(hierarchical,network and laissez-faire governance)and budget policies.The simulation shows that it is possible to mimic SDI governance dynamics through agent-based modelling.By running different scenarios,it appears that a network approach is more successful compared to a hierarchical or laissez-faire approach.Expert validation shows that overall the results of the simulation are credible and insightful,although improvements can be made to make the model more realistic.With agent-based modelling,SDI governance becomes more tangible and visible,which facilitates discussion and understanding.Agent-based modelling therefore appears to be a helpful new approach in a better understanding of the complexities and dynamics of SDI governance.