Showing papers on "Complex adaptive system published in 2004"

Rethinking Community‐Based Conservation

Abstract: Community-based conservation (CBC) is based on the idea that if conservation and development could be simultaneously achieved, then the interests of both could be served. It has been controversial because community development objectives are not necessarily consistent with conservation objectives in a given case. I examined CBC from two angles. First, CBC can be seen in the context of paradigm shifts in ecology and applied ecology. I identified three conceptual shifts—toward a systems view, toward the inclusion of humans in the ecosystem, and toward participatory approaches to ecosystem management—that are interrelated and pertain to an understanding of ecosystems as complex adaptive systems in which humans are an integral part. Second, I investigated the feasibility of CBC, as informed by a number of emerging interdisciplinary fields that have been pursuing various aspects of coupled systems of humans and nature. These fields—common property, traditional ecological knowledge, environmental ethics, political ecology, and environmental history—provide insights for CBC. They may contribute to the development of an interdisciplinary conservation science with a more sophisticated understanding of social-ecological interactions. The lessons from these fields include the importance of cross-scale conservation, adaptive comanagement, the question of incentives and multiple stakeholders, the use of traditional ecological knowledge, and development of a cross-cultural conservation ethic.

Adaptive comanagement for building resilience in social-ecological systems.

Abstract: Ecosystems are complex adaptive systems that require flexible governance with the ability to respond to environmental feedback. We present, through examples from Sweden and Canada, the development of adaptive comanagement systems, showing how local groups self-organize, learn, and actively adapt to and shape change with social networks that connect institutions and organizations across levels and scales and that facilitate information flows. The development took place through a sequence of responses to environmental events that widened the scope of local management from a particular issue or resource to a broad set of issues related to ecosystem processes across scales and from individual actors, to group of actors to multiple-actor processes. The results suggest that the institutional and organizational landscapes should be approached as carefully as the ecological in order to clarify features that contribute to the resilience of social-ecological systems. These include the following: vision, leadership, and trust; enabling legislation that creates social space for ecosystem management; funds for responding to environmental change and for remedial action; capacity for monitoring and responding to environmental feedback; information flow through social networks; the combination of various sources of information and knowledge; and sense-making and arenas of collaborative learning for ecosystem management. We propose that the self-organizing process of adaptive comanagement development, facilitated by rules and incentives of higher levels, has the potential to expand desirable stability domains of a region and make social-ecological systems more robust to change.

Real-world market representation with agents

Abstract: As power markets are relatively new and still continue to evolve, there is a growing need for advanced modeling approaches that simulate the behavior of electricity markets over time and how market participants may act and react to the changing economic, financial and regulatory environments in which they operate. A new and rather promising approach is to model the electricity market as a complex adaptive system using an agent-based modeling and simulation (ABMS) approach. The purpose of an ABMS model is not necessarily to predict the outcome of a system but to reveal and understand the complex and aggregate system behaviors that emerge from the interactions of the heterogeneous individual entities. Emergent behavior is a key feature of ABMS and is not easily inferred from the simple sum of the behavior of its components. By relying on both established engineering modeling techniques as well as advanced quantitative economic market principles, the ABMS approach is uniquely suited to addressing the strategic issues of interest to different market participants as well as those of market monitors and regulators.

Coordination in complex systems: increasing efficiency in disaster mitigation and response

Abstract: Coordination in multi-organisational settings is extraordinarily difficult to achieve. This article examines the problem of inter-organisational coordination in the context of public administration theory and practice. The authors present the concept of complex adaptive systems as a theoretical framework that explains the dynamic processes involved in achieving coordinated action among multiple organisations to manage complex technical operations in environments vulnerable to risk. They argue that coordination may be achieved more easily with the appropriate design of a socio-technical system, that is, a system that supports the exchange of critical information among technical and organisational entities to improve performance in both. The goal is to design a decision support system that uses information technology to enhance the capacity of multiple organisations to adapt their actions reciprocally to changing conditions of risk, enabling the set of organisations to manage risk more effectively and efficiently for the community as a whole. The authors present the design and initial findings from a trial demonstration to implement a prototype interactive, intelligent, spatial information system in the Pittsburgh Metropolitan Region.

Assessing infrastructure interdependencies: the challenge of risk analysis for complex adaptive systems

Abstract: Infrastructures are a complex set of interconnected, interdependent, adaptive systems on which the nation, manufacturing systems and individuals depend. Understanding the potential consequences of infrastructure interdependencies, as the infrastructures evolve and the regulations governing their operation change, is at the heart of our infrastructure interdependencies research program. This program includes development of analysis methods and simulation tools for evaluating the potential effects of disruptions and for prioritising risks. Fundamental infrastructures simulated using these tools include; transportation, telecommunications, electric power, banking and finance, water, agriculture, emergency services, fossil fuels, and government. The complexity of the infrastructures and their interactions prevent us from knowing a priori how these interactions will influence individuals, states or the nation; the consequences of policy decisions; vulnerabilities due to interdependencies, natural disasters, malevolent threats and aging; or vulnerabilities that need to be eliminated in order to assure individual, state or national economic security. The goal of the interdependency analyses is to identify significant risks to critical systems, arising from interconnection, and effective mechanisms for mitigating those risks. This article presents the infrastructure interdependency assessment process, modelling tools developed to support that process and examples of assessment results.

Artificial War: Multiagent-Based Simulation of Combat

Abstract: Military conflicts, particularly land combat, possess all of the key attributes of complex adaptive systems: combat forces are composed of many nonlinearly interacting parts and are organized in a dynamic command-and-control hierarchy; local action, which often appears disordered, self-organizes into long-range order; military conflicts, by their nature, proceed far from equilibrium; military forces adapt to a changing combat environment; and there is no master "voice" that dictates the actions of every soldier (i.e., battlefield action is decentralized). Nonetheless, most modern "state of the art" military simulations ignore the self-organizing properties of combat. This book develops the proposition that combat is more like an interpenetration of two living, coevolving fluids rather than an elastic collision between two hard billiard balls. Artificial-life techniques - specifically, multiagent-based models coupled with evolutionary learning algorithms - provide a powerful new approach to understanding the fundamental processes of war. The book introduces an artificial-life model of combat called EINSTein. Recently developed at the Center for Naval Analyses, USA by the author, EINSTein is one of the first systematic attempts to simulate combat on a small-to-medium scale by using autonomous agents to model individual behaviors and personalities rather than hardware. EINSTein shows that many aspects of land combat may be understood as self-organized, emergent phenomena resulting from the dynamic web of interactions among coevolving agents. Thus, its bottom-up, synthesist approach to modeling combat stands in vivid contrast to the current top-down, reductionist approach taken by conventional models. EINSTein is the first step toward a complex-systems-theoretic toolbox for identifying, exploring, and exploiting self-organized emergent patterns of behavior on the real battlefield.

Organizational survival in the new world : the intelligent complex adaptive system : a new theory of the firm

Abstract: Moving Beyond the Bureaucratic Model The Present and Future Danger or Why We Need To Change The Intelligent Complex Adaptive System (ICAS) Exploring the Emergent Properties of ICAS Relationships Among Emergent Properties The Learning Structure of the New Organization The Action Culture for Success The Four Major Organizational Processes The Art of Collaborative Leadership Creating Emergence The Change Agent's Strategy Strategy, Balance and the Correlation of Forces A Tale of Two Companies The New Knowledge Worker Knowledge Management The Learning Organization Learning, KM and Knowledge Workers Rethinking Thinking: Systems Rethinking Thinking: Complexity Knowing Networking for the Bottom Line Exploring the Unknown APPENDIX: The Evolution of the Organization. GLOSSARY BIBLIOGRAPHY INDEX

International Entrepreneurship as a Dynamic Adaptive System: Towards a Grounded Theory

Abstract: This paper is based on a primary assumption: That the internationalizing smaller firms are dif- ferent from large international firms, such as multinational enterprises (MNEs); and therefore, the process of internationalization and growth of smaller firms may not follow processes stipulated in the extant theories of MNEs and international business processes (IBPs). Even the primary orientations and theoretical constructs used in IBP and the theory of multinationals are different from those in entrepreneurship: While the former focuses on the institution of the "firm" the latter concentres on the "entrepreneur" as internationalizing entities. This paper will suggest a theoretical framework capable of integrating this prevailing fragmentation. The framework is based on the tenets of dynamic open complex adaptive system (DOCAS), compris- ing three layers, reflecting entrepreneurs (or entrepreneurial teams), firms and markets to reflect their own dynamics as well as the inter-relations and interactions of entities within and across layers within the frame- work. After a brief review of the basic characteristics of a simple DOCAS and the major attributes of entities populating each layer in the framework, the interdependencies and interactions within and across layers are highlighted. This framework presents a coherent and comprehensive structure capable of housing the next six papers contained in this issue. They are reviewed and highlighted from the perspective of the proposed framework. These papers support the proposed framework substantively. The proposed grounded frame- work appears to lay the foundation for the research and theory necessary for enhancing our understanding of IBP and internationalization in smaller firms. Conclusion and implications of the papers are presented at the end.

Military applications of agent-based simulations

Abstract: There continues to be increasing interest from a broad range of disciplines in agent-based and artificial life simulations. This includes the Department of Defense - which uses simulations heavily in its decision making process. Indeed, military conflicts can have many attributes that are consistent with complex adaptive systems - such as many entities interacting with some degree of autonomy, each of which is continually making decisions to satisfy a variety of sometimes conflicting objectives. In this paper, we present three applications of agent-based simulations used to analyze military problems. The first uses the MANA model to explore the ability of the U.S. Army's network-based Future Force to perform with degraded communications. The second studies how unmanned surface vehicles can be used in force protection missions with the Pythagoras model. The last example examines the standard Army squad size with an integrated effort using MANA, Pythagoras, and the high-resolution simulation JANUS.

Manufacturing strategy: understanding the fitness landscape

Abstract: This theoretical paper presents, extends and integrates a number of systems and evolutionary concepts, to demonstrate their relevance to manufacturing strategy formulation. Specifically it concentrates on fitness landscape theory as an approach for visually mapping the strategic options a manufacturing firm could pursue. It examines how this theory relates to manufacturing competitiveness and strategy and proposes a definition and model of manufacturing fitness. In accordance with fitness landscape theory, a complex systems perspective is adopted to view manufacturing firms. It is argued that manufacturing firms are a specific type of complex system – a complex adaptive system – and that by developing and applying fitness landscape theory it is possible to create models to better understand and visualise how to search and select various combinations of capabilities.

Scale, Complexity and the Representation of Theories of Change

Abstract: International aid agencies face major problems when attempting to evaluate their achievements. Activities, intended beneficiaries, partner institutions and social contexts are diverse because of their global scale. How can agencies’ ‘theories of change’ be adequately represented in summary forms that respect the complexity and diversity? This article, the first of two, looks at a range of types of change processes and how they can be represented. It starts with linear processes, traditionally represented via the Logical Framework, and ends with network processes. The solutions proposed are informed by three related cross-disciplinary theoretical perspectives: evolutionary theory; complex adaptive systems; and social network analysis. Examples draw on the author’s consultancy experience with international development aid programmes in Vietnam, Bangladesh, Cameroon and Burkina Faso.

The standing ovation problem

Abstract: Over the last decade, research topics such as learning, heterogeneity, networks, diffusion, and externalities, have moved from the fringe to the frontier in the social sciences. In large part this new research agenda has been driven by key tools and ideas emerging from the study of complex adaptive systems. Research is often inspired by simple models that provide a rich domain from which to explore the world. Indeed, in complex systems, Bak’s (1996) sand pile, Arthur’s (1994) El Farol bar, and Kauffman’s (1989) NK system have provided such inspirations. Here we introduce another model that offers similar potential—the Standing Ovation Problem (SOP). This model is especially appropriate given the focus of this special issue on complex adaptive social systems. The SOP has much to offer as it (1) is easily explained and part of everyone’s common experience; (2) simultaneously emphasizes some of the key themes that arise in social systems, such as learning, heterogeneity, incentives, and networks; and (3) is amenable to research efforts across a variety of fields. These features make it an ideal platform from which to explore the power, promise, and pitfalls of complexity modeling in the social sciences. The basic SOP can be stated as: A brilliant economics lecture ends and the audience begins to applaud. The applause builds and tentatively, a few audience members may or may not decide to stand. Does a standing ovation ensue or does the enthusiasm fizzle? Inspired by the seminal work of Schelling (1978), the SOP possesses sufficient structure to generate nontrivial dynamics without imposing too many a priori modeling constraints. Like Schelling’s work, it focuses on the macro-behavior that emerges from micro-motives, and relies on models that emphasize agents driven by simple behavioral algorithms placed in interesting spatial contexts. Though ostensibly simple, the social dynamics responsible for a standing ovation are complex. As the performance ends, each audience member must decide whether or not to stand. Of course, if the decision to stand is simply a personal choice based on the individual’s own assessment of the worth of the performance, the problem becomes trivial. However, people do not stand solely based upon their own impressions of the performance. A seated audience member surrounded by people standing might be enticed to stand, even if he hated the performance. This behavioral mimicry could be strategic (the agents wants to send the

Behaviour as a Complex Adaptive System: On the Role of Self-Organization in the Development of Individual and Collective Behaviour

Abstract: In this paper we discuss the complex system and adaptive nature of behaviour. The complex system nature of behaviour derives from the fact that behaviour and behavioural properties are phenomena that occur at a given time scale and result from several non-linear interactions occurring at a smaller time scale. Interactions occur in time (i.e. consist of sequence events in which future interactions are constrained by preceding interactions) and might eventually consist of a vector of concurrent interactions. Moreover, we argued that behaviour might involve several emergent dynamical processes, hierarchically organized, that affect each other bottom-up and top-down. The adaptive system nature of behaviour derives from the fact that, due to the very indirect relationship between the properties of the interacting elements and the emergent results of the interactions, behavioural systems can hardly be designed while they can be effectively developed through self-organizing methods in which properties emerging from interactions can be discovered and retained through an adaptive process based on exploration and selection. These two claims will be demonstrated in two concrete examples involving mobile robots in which non-trivial individual and collective behaviours have been developed through an evolutionary technique.

A Mechanism for Pockets of Predictability in Complex Adaptive Systems

Abstract: We document a mechanism operating in complex adaptive systems leading to dynamical pockets of predictability (``prediction days''), in which agents collectively take predetermined courses of action, transiently decoupled from past history. We demonstrate and test it out-of-sample on synthetic minority and majority games as well as on real financial time series. The surprising large frequency of these prediction days implies a collective organization of agents and of their strategies which condense into transitional herding regimes.

Organizational Survival in the New World

Abstract: In this book David and Alex Bennet propose a new model for organizations that enables them to react more quickly and fluidly to today's fast-changing, dynamic business environment: the Intelligent Complex Adaptive System (ICAS) ICAS is a new organic model of the firm based on recent research in complexity and neuroscience, and incorporating networking theory and knowledge management, and turns the living system metaphor into a reality for organizations This book synthesizes new thinking about organizational structure from the fields listed above into ICAS, a new systems model for the successful organization of the future designed to help leaders and managers of knowledge organizations succeed in a non-linear, complex, fast-changing and turbulent environment Technology enables connectivity, and the ICAS model takes advantage of that connectivity by fostering the development of dynamic, effective and trusting relationships in a new organizational structure This book outlines the model in chapter four, and then breaks down the model into its components in the next two chapters This is a benefit to readers since different components of the model can be implemented at different times, so the book can guide implementation of one or all of the components as a manager sees fit There are eight characteristics of the ICAS: organizational intelligence, unity and shared purpose, optimum complexity, selectivity, knowledge centricity, flow, permeable boundaries, and multi-dimensionality

On Selfish Memes: culture as complex adaptive system

Abstract: We present the formal definition of meme in the sense of the equivalence between memetics and the theory of cultural evolution. From the formal definition we find that culture can be seen analytically and persuade that memetic gives important role in the exploration of sociological theory, especially in the cultural studies. We show that we are not allowed to assume meme as smallest information unit in cultural evolution in general, but it is the smallest information we use on explaining cultural evolution. We construct a computational model and do simulation in advance presenting the selfish meme powerlaw distributed. The simulation result shows that the contagion of meme as well as cultural evolution is a complex adaptive system. Memetics is the system and art of importing genetics to social sciences.

Leadership in Complex Systems: Meta-Level Information Processing Capabilities that Bias Exploration and Exploitation

Abstract: Organizations as complex systems face the challenge of continuing operations as well as surviving in a constantly changing environment. This challenge is often framed in the context of strategic leadership – leaders are seen as managing the tension between exploration and exploitation (March, 1991). This study looks at how leadership and the actions of leaders relate to this tension. The analysis looks at the organization as a complex dynamic system interacting and co-evolving with a changing environment. It looks at leadership capability as a meta-level information processing capability that serves over time to bias the system toward one or the other of performance or adaptation in response information signals from the environment. Propositions regarding the importance of leadership defined in this way are presented, and a model of organizations as complex adaptive systems is described. Using a system dynamics implementation, the model is used in a series of virtual experiments to test the propositions. In general, the notion of adaptive agency at the organizational level due to the presence of leadership capability is supported.

Marketing management in a complex adaptive system

Abstract: This article explores how complexity theory can help marketers to understand a market and to operate within it. Essentially, it argues that complexity theory has the potential to provide both global and some local explanations of markets and is complementary to local theories like relationship marketing that may be more familiar to marketing managers. It establishes four types of complex systems that might be used to model social systems. Of these four types, complex adaptive systems seem most appropriate to describe markets. This is illustrated in an investigation of Honda in the global automobile industry. Implications for marketing managers centre on the need to understand feedback loops at many levels of a path‐dependent system that are inherently difficult to predict and control.

Modeling Power Systems as Complex Adaptive Systems

Abstract: Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

Monitoring in a complex world — seeking slow variables, a scaled focus, and speedier learning

Abstract: Recent developments from complex systems theorists provide new insights into our understanding and, hence, monitoring of rangelands. Designing monitoring systems around the slow variables should lead to the generation of information that could greatly improve decision making in an adaptive management context. Monitoring can also be far better focused on supporting faster development of local environmental knowledge when traditional experiential learning modes cannot always keep up with the increasingly rapid pace of change in rangelands. After casting the design and purpose of monitoring systems in theoretical terms, the authors draw on applications from southern Africa to confront these conceptual approaches with real world practice. Using two cases, one from a community based agro-pastoral system and the other from a conservation area, the authors examine how the theory and practice inform monitoring systems design. Does theory really guide us in developing useful monitoring systems when faced with the ...

Acquisition of Complex Systemic Thinking: Mental Models of Evolution

Abstract: We investigated the impact of introducing college students to complex adaptive systems on their subsequent mental models of evolution compared to those of students taught in the same manner but with no reference to complex systems. The students' mental models (derived from similarity ratings of 12 evolutionary terms using the pathfinder algorithm) were significantly similar to their teachers' mental models and were correlated to their performance on an essay on evolution. Introducing students to complex systems facilitated their understanding of the mechanism of inheritance, the mechanism of evolution, and the role of chance in evolution.

Intelligence strategy: the evolutionary and co-evolutionary dynamics of intelligent human organizations and their interacting agents

Abstract: In the knowledge economy, the human minds are the most vital center of analysis. They are the complex adaptive systems capable of processing information, establishing knowledge structure, conceptualizing idea, and making decision. The intrinsic intelligence of the individual minds, as well as the organizational/collective intelligence, drives the dynamic of all human systems. Primarily, the local self-enrichment processes of the interacting agents are autopoietic. In addition, global forces are also present in all human organizations. The global forces are constructive only if they support the elementary processes. The global forces originate from the orgmind of the organization. A complex relationship exists between the interacting agents and their systems. Traditionally, the decision-making dynamic of the human thinking systems has been dealt with in economics concepts such as the "economic" man that focuses on perfect rational decision, and Herbert Simon's "administrative" man that incorporates the idea of bounded rationality. In this study, the dynamic of an "intelligent" person is introduced. An intelligent person does not concentrate on optimality at all times. Instead, such a person adopts the intelligence strategy. An intelligent person is mindful and contributes continuously towards the collective intelligence of the system. The mindset of an intelligent person encompasses continual fast learning, longer-term survival, exploitation of the butterfly effect, and co-evolution with his/her system. In this respect, an intelligent person is a rather dissimilar interacting agent.

The social dynamics of diverse and closed networks

Abstract: Inherent to the dynamics of social networks is a paradoxical trade-off between closed networks that promote cooper- ation and efficiency and diverse networks that are flexible to new resources and ideas. Since actors cannot simultaneously max- imize both facets of a network, this has created a sharp debate on the social capital performance of closed and diverse network relationships. Research on this social capital debate has often focused on these described network affects without explaining the origins and dynamics of network performance. This paper advances a cognitive diversity approach that is based upon the subjec- tive and alert behaviors of Austrian entrepreneurs. These are key causal drivers to this paper's theoretical model of social dynam- ics and performance of closed and diverse networks. Such network behavior is subsequently modeled as a Complex Adaptive system. Using agent-based simulation, an agent-based model of entrepreneurship and social network dynamics is constructed to test the relationships described by the proposed theoretical model. The simulation results support the described hypothesized relationships. These findings also suggest the benefits of closed and diverse networks are logically distinct and, thus, should not be viewed as an either-or phenomenon. Agent-based simulation results show entrepreneurs can construct a balanced network of closed and diverse networks to optimize the benefits of both networks.

Study on Complex Adaptive System and Agent-Based Modeling&Simulation

Abstract: The complexity has been analyzed from two aspects: epistemology and methodology angle .Through discussing the forms of complexity in complex systems, we hold that complexity is the essential property of the objective world, and its research method must be holism. It is pointed out that the effective way to research complex system is system simulation. A descriptive definition for complex system is presented. Then the theory of Complex Adaptive System (CAS) and its research method, called agent-based modelingsimulation (ABMS) methodology are introduced. The applications of ABMS in several fields are also stated and agent-based modeling method is discussed in depth. The paper ends with the current and future research works on ABMS in astronautics engineering system domain.

A complex systems approach for developing public policy toward terrorism: an agent-based approach

Abstract: This paper examines terrorist “fluids” as complex adaptive systems. The principles of agent-based modeling are applied to global terrorism as a basis for developing agent-based models of terrorist behavior. Recommendations for agent-based models of terrorist behavior as policy analytic tools are presented.

Mapping the Information System Development Process

Abstract: Action research is used to gain understanding of how an IS development methodology emerges in practice and how it can contribute to value creation in organizations. The Multiview framework is used to guide the action research project. A graphical notation for mapping the unfolding of IS development projects is developed and applied to the project. Reflection on the project leads to a number of lessons being drawn about the organization of the IS development process, addressing themes such as vision, time pacing, and the role of architecture. The paper concludes with ideas about how the theoretical underpinnings of IS development might be bolstered by complex adaptive systems.

Outcomes-based education versus coping with complexity: should we be educating for capability?

Abstract: The process of education can be likened to a complex adaptive system whereby a collection of individual agents... [have] freedom to act in ways that are not always totally predictable 3 (p. 625). In such a system, fuzzy boundaries between different parts of the system exist, agents within the system are changeable over time and tension within the system is natural and valued. However, in outcomesbased education we try to reduce a complex adaptive system to its constituent parts by precisely defining the knowledge, skills and attitudes to be acquired by our students.

Statistical mechanics: a possible model for market-based electric power control

Abstract: Statistical mechanics provides a useful analog for understanding the behavior of complex adaptive systems, including electric power markets and the power systems they intend to govern. Market-based control is founded on the conjecture that the regulation of complex systems based on price-mediated strategies (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This paper discusses the derivation and some illustrative applications of a first-principles model of market-based system dynamics based on strict analogies to statistical mechanics.