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.

APPLICATION STUDY ON ADAPTIVE NEURAL FUZZY INFERENCE MODEL IN COMPLEX SOCIAL-TECHNICAL SYSTEM

The adaptive neural fuzzy inference system （ANFIS） is used to make a ease study considering features of complex social-technical system with the target of increasing organizational efficiency of public scientific research institutions. An integrated ANFIS model is built and the effectiveness of the model is verified by means of investigation data and their processing results. The model merges the learning mechanism of neural network and the language inference ability of fuzzy system, and thereby remedies the defects of neural network and fuzzy logic system. Result of this case study shows that the model is suitable for complicated socio-technical systems and has bright application perspective to solve such problems of prediction, evaluation and policy-making in managerial fields.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

Decentralized Adaptive Strategies for Synchronization of Fractional-order Complex Networks

This paper focuses on synchronization of fractionalorder complex dynamical networks with decentralized adaptive coupling.Based on local information among neighboring nodes,two fractional-order decentralized adaptive strategies are designed to tune all or only a small fraction of the coupling gains respectively.By constructing quadratic Lyapunov functions and utilizing fractional inequality techniques,Mittag-Leffler function,and Laplace transform,two sufficient conditions are derived for reaching network synchronization by using the proposed adaptive laws.Finally,two numerical examples are given to verify the theoretical results.

Adaptive generalized matrix projective lag synchronization between two different complex networks with non-identical nodes and different dimensions

The adaptive generalized matrix projective lag synchronization between two different complex networks with non-identical nodes and different dimensions is investigated in this paper. Based on Lyapunov stability theory and Barbalat＇s lemma, generalized matrix projective lag synchronization criteria are derived by using the adaptive control method. Furthermore, each network can be undirected or directed, connected or disconnected, and nodes in either network may have identical or different dynamics. The proposed strategy is applicable to almost all kinds of complex networks. In addition, numerical simulation results are presented to illustrate the effectiveness of this method, showing that the synchronization speed is sensitively influenced by the adaptive law strength, the network size, and the network topological structure.

Model for cascading failures with adaptive defense in complex networks

This paper investigates cascading failures in networks by considering interplay between the flow dynamic and the network topology, where the fluxes exchanged between a pair of nodes can be adaptively adjusted depending on the changes of the shortest path lengths between them. The simulations on both an artificially created scale-free network and the real network structure of the power grid reveal that the adaptive adjustment of the fluxes can drastically enhance the robustness of complex networks against cascading failures. Particularly, there exists an optimal region where the propagation of the cascade is significantly suppressed and the fluxes supported by the network are maximal. With this understanding, a costless strategy of defense for preventing cascade breakdown is proposed. It is shown to be more effective for suppressing the propagation of the cascade than the recent proposed strategy of defense based on the intentional removal of nodes.

Understanding leukemic hematopoiesis as a complex adaptive system

Normal and abnormal hematopoiesis is working as a complex adaptive system. From this perspective, the development and the behavior of hematopoietic cell lineages appear as a balance between normal and abnormal hematopoiesis in the setting of a functioning or malfunctioning microenvironment under the control of the immune system and the influence of hereditary and environmental events.

Robust adaptive synchronization of uncertain and delayed dynamical complex networks with faulty network

This paper presents a new robust adaptive synchronization method for a class of uncertain dynamical complex networks with network failures and coupling time-varying delays. Adaptive schemes are proposed to adjust controller parameters for the faulty network compensations, as well as to estimate the upper and lower bounds of delayed state errors and perturbations to compensate the effects of delay and perturbation on-line without assuming symmetry or irreducibility of networks. It is shown that, through Lyapunov stability theory, distributed adaptive controllers con- structed by the adaptive schemes are successful in ensuring the achievement of asymptotic synchronization of networks in the present of faulty and delayed networks, and perturbation inputs. A Chua＇s circuit network example is finally given to show the effectiveness of the proposed synchronization criteria.

Adaptive function projective synchronization of uncertain complex dynamical networks with disturbance

We investigate the problem of function projective synchronization （FPS） in drive–response dynamical networks with non-identical nodes. An adaptive controller is proposed for the FPS of complex dynamical networks with uncertain parameters and disturbance. Not only are the unknown parameters of the networks estimated by the adaptive laws obtained from the Lyapunov stability theory and Taylor expansions, but the unknown bounded disturbances are also simultaneously conquered by the proposed control. Finally, a numerical simulation is provided to illustrate the feasibility and effectiveness of the obtained result.

A Comment on Language Is a Complex Adaptive System: Position Paper

Language not only functions as a communication tool,it has fundamental functions.People’s social interaction and their past experience can affect people’s choice of language,as language is a complex,adaptive system.The paper tries to comment on"A comment on Language Is a Complex Adaptive System:Position Paper"from several aspects to conclude that Language Is a Complex Adaptive System:Position Paper is a comprehensive,creative and influential academic paper which is characteristic of high originality,well-compact organization,detailed literature review.

Decentralized adaptive synchronization of an uncertain complex delayed dynamical network

In this paper, we investigate the locally and globally adaptive synchronization problem for an uncertain complex dynamical network with time-varying coupling delays based on the decentralized control. The coupling terms here are bounded by high-order polynomials with known gains that are ubiquitous in a large class of complex dynamical networks. We generalize the usual technology of searching for an appropriate coordinates transformation to change the network dynamics into a series of decoupled lower-dimensional systems. Several adaptive synchronization criteria are derived by constructing the Lyapunov-Krasovskii functional and Barbalat lemma, and the proposed criteria are simple in form and convenient for the practical engineering design. Numerical simulations illustrated by a nearest-neighbor coupling network verify the effectiveness of the proposed synchronization scheme.

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.

Quasi-optimal complexity of adaptive finite element method for linear elasticity problems in two dimensions

This paper introduces an adaptive finite element method （AFEM） using the newest vertex bisection and marking exclusively according to the error estimator without special treatment of oscillation. By the combination of the global lower bound and the localized upper bound of the posteriori error estimator, perturbation of oscillation, and cardinality of the marked element set, it is proved that the AFEM is quasi-optimal for linear elasticity problems in two dimensions, and this conclusion is verified by the numerical examples.

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.

Dynamic modeling and aperiodically intermittent strategy for adaptive finite-time synchronization control of the multi-weighted complex transportation networks with multiple delays

The idea of network splitting according to time delay and weight is introduced.Based on the cyber physical systems(CPS),a class of multi-weighted complex transportation networks with multiple delays is modeled.The finite-time synchronization of the proposed complex transportation networks model is studied systematically.On the basis of the theory of stability,the technique of adaptive control,aperiodically intermittent control and finite-time control,the aperiodically intermittent adaptive finite-time synchronization controller is designed.The controller designed in this paper is beneficial for understanding the synchronization in multi-weighted complex transportation networks with multiple delays.In addition,the conditions for the existence of finite time synchronization have been discussed in detail.And the specific value of the settling finite time for synchronization is obtained.Moreover,the outer coupling configuration matrices are not required to be irreducible or symmetric.Finally,simulation results of the finite-time synchronization problem are given to illustrate the correctness of the results obtained.

Lyapunov-Based Dynamic Neural Network for Adaptive Control of Complex Systems

In this paper, an adaptive neuro-control structure for complex dynamic system is proposed. A recurrent Neural Network is trained-off-line to learn the inverse dynamics of the system from the observation of the input-output data. The direct adaptive approach is performed after the training process is achieved. A lyapunov-Base training algorithm is proposed and used to adjust on-line the network weights so that the neural model output follows the desired one. The simulation results obtained verify the effectiveness of the proposed control method.

Linguistic Reflection on the Online Catchword of Appreciation —From the Perspective of Usage-based Language Model and Complex Adaptive System Theory

Language is a special social phenomenon and is always on the changing process with the development of society. During the evolving process of language, new language varieties will continuously emerge due to the changes of some social and cultural factors. Cyber language is universally accepted as one type of the social language varieties. Basically, cyber language can be treated as a complex adaptive system which is influenced by the interaction between users’ cognition, social culture and the surrounding environments. Thus it is safe to say that cyber language is always undergoing a dynamic evolving process. With the usage-based language model as the theoretical foundation, this paper proposes a Complex Adaptive System (CAS) approach to analyze the expression of Appreciation to explore the complex, dynamic and nonlinear development of cyber language from the angle of meaning construction, grammaticalization and functional adaption respectively. It is found that the expression of Appreciation is experiencing adaptively a semantic connotations development and a process of grammatical functions expansion as well. This paper suggests that the emergence and development of cyber language is a novel and trendy social language phenomenon. Network language can achieve its process and evolution under the huge impact of social changes and social promotions. When faced with the changing surroundings, cyber language itself enjoys a timely adaption and responsive development to keep up with the new environments, which reflects the basic principle of language development, namely, language changes with the development of society.

An exploratory study of the growth of the Accountable Care Organization and its impact on physician groups’ profit: a complex adaptive system approach

The emergence of Accountable Care Organizations(ACOs)in the landscape of the U.S.healthcare system marks a paradigm shift in healthcare operations.The potential impact of ACOs has been a topic of intense debate.Traditional analytical approaches do not lend themselves to examining the complex phenomenon of the emergence and growth of ACOs in the healthcare network.We adopt a complex adaptive system lens to examine the growth of ACOs among physician groups and explore factors that influence this growth.We also discuss the impact of ACOs on the profit of physician groups.An agent-based model was built to simulate physician groups'ACO entrance and exit based on a set of simple rules and their complex interactions with other agents.Based on the simulation results,we derive patterns of ACO expansion and contraction,following four stages of wait-and-see,rollercoaster,fast growth,and stabilizing.Findings suggest that the growth of ACOs is sensitive to the initial state of ACO membership.When the initial size of ACO membership increases,it helps to eliminate the rollercoaster stage.In addition,the growth of the ACO varies depending on the cost–quality tradeoff.When both cost and quality objectives can be met simultaneously,the growth of ACO membership follows wait-and-see and fast growth stages followed by a different stage that we term sticky state.The impact of ACOs on physician groups’cumulative profit varies by the service quality level of the physician group.Physician groups affiliated with insurance companies charging the lowest or the highest level of health insurance premiums are worse off with the ACO option.However,the ACO benefits physician groups affiliated with an insurance company charging a moderate level of premiums.

Chromatic Adaptation to Complex Field

Chromatic adaptation of human eyes to complex field is investigated using binocular asymmetric matching method. The results show that the leve of chromatic adapta- tion mainly depends on the average color of adapting field, whereas no obvious change oc- curs when the number of hues and their color differences vary in a complex field. The shifts of perceived color evoked by chromatic adaptation in CIE 1976 L U V color space are approximately proportional to the average color difference between the adapting field and reference field.

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.