Resilience Of Complex Systems Research Articles

A simulation and experimentation architecture for resilient cooperative multiagent reinforcement learning models operating in contested and dynamic environments

Cooperative multiagent reinforcement learning approaches are increasingly being used to make decisions in contested and dynamic environments, which tend to be wildly different from the environments used to train them. As such, there is a need for a more in-depth understanding of their resilience and robustness in conditions such as network partitions, node failures, or attacks. In this article, we propose a modeling and simulation framework that explores the resilience of four c-MARL models when faced with different types of attacks, and the impact that training with different perturbations has on the effectiveness of these attacks. We show that c-MARL approaches are highly vulnerable to perturbations of observation, action reward, and communication, showing more than 80% drop in the performance from the baseline. We also show that appropriate training with perturbations can dramatically improve performance in some cases, however, can also result in overfitting, making the models less resilient against other attacks. This is a first step toward a more in-depth understanding of the resilience c-MARL models and the effect that contested environments can have on their behavior and toward resilience of complex systems in general.

Resilience of complex systems in modern contexts: sense-making of deviations and enabling the human for mitigating unwanted events and incidents

Resilience of complex systems in modern contexts: sense-making of deviations and enabling the human for mitigating unwanted events and incidents

Complex Systems of Property: Change and Resilience After a Catastrophic Disaster

Abstract This Article applies emerging literature on resilience in complex systems to institutional change in property rights systems. Complex systems theory provides an alternative to economic models that adopt assumptions of linearity in property rights transitions—where inputs such as rising resource values induce proportionate outputs in the formation of private property rights. Based on a case study of catastrophic disaster, the Article concludes that institutional change in a complex property system does not involve proportionate or predictable responses to sudden shocks in the external environment. The stochasticity of institutional change arises from acts of adaptive self-organization across multiple scales of proprietary governance. The “added value” of systems theory is a set of conceptual tools—such as scale, stochasticity, and self-organization—which help to explain resilience and change in property systems affected by sudden environmental shocks.

Uncertainty quantification of multi-scale resilience in networked systems with nonlinear dynamics using arbitrary polynomial chaos

Complex systems derive sophisticated behavioral dynamics by connecting individual component dynamics via a complex network. The resilience of complex systems is a critical ability to regain desirable behavior after perturbations. In the past years, our understanding of large-scale networked resilience is largely confined to proprietary agent-based simulations or topological analysis of graphs. However, we know the dynamics and topology both matter and the impact of model uncertainty of the system remains unsolved, especially on individual nodes. In order to quantify the effect of uncertainty on resilience across the network resolutions (from macro-scale network statistics to individual node dynamics), we employ an arbitrary polynomial chaos (aPC) expansion method to identify the probability of a node in losing its resilience and how the different model parameters contribute to this risk on a single node. We test this using both a generic networked bi-stable system and also established ecological and work force commuter network dynamics to demonstrate applicability. This framework will aid practitioners to both understand macro-scale behavior and make micro-scale interventions.

Reliability analysis and resilience measure of complex systems in shock events

<abstract> <p>The working environment of complex systems is complex and variable, and their performance is often affected by various shock events during the service phase. In this paper, first, considering that the system performance will be affected by shocks again in the process of maintenance, the reliability changes and fault process of complex systems are discussed. Second, the performance change processes of complex systems are analyzed under multiple shocks and maintenance. Then, based on performance loss and recovery, this paper analyzes the reliability and resilience of complex systems under the intersecting process of multiple shocks and maintenance. Considering the direct and indirect losses caused by shocks, as well as maintenance costs, the changes in total costs are analyzed. Finally, the practicability of the proposed model is checked by using a specific welding robot system.</p> </abstract>

Resiliência em saúde pública: preceitos, conceitos, desafios e perspectivas

ABSTRACT In a health system, resilience is manifested in the ability to adapt to demands or to adverse and disruptive events, such as epidemics and/or disasters, adjusting its functioning to stressful situations, before, during or after these exceptional disturbances, while maintaining the functioning and quality of assistance, thus preserving its regular activities and properties. In this essay, we present some concepts about resilience in complex systems and their applications in health systems and organizations, involving the resilience of individuals, teams, and organizations. Challenges and perspectives for improving the resilient behavior of the Brazilian Unified Health System (SUS) are also highlighted, a topic that has gained enormous attention in the COVID-19 pandemic. We conclude by emphasizing the need for more research on the various topics involving resilience in healthcare to strengthen the capacity of the SUS to cope with both daily challenges and future health crises.

Towards an Analytic Framework for System Resilience Based on Reaction Networks

Reaction network is a promising framework for representing complex systems of diverse and even interdisciplinary types. In this approach, complex systems appear as self‐maintaining structures emerging from a multitude of interactions, similar to proposed scenarios for the origin of life out of autocatalytic networks. The formalism of chemical organization theory (COT) mathematically specifies under which conditions a reaction network is stable enough to be observed as a whole complex system. Such conditions specify the notion of organization, crucial in COT. In this paper, we show that the structure and operation of organizations can be advanced towards a formal framework of resilience in complex systems. That is, we show that there exist three fundamental types of change (state, process, and structural) defined for reaction networks, and that these perturbations not only provide a general representation of perturbations in the context of resilience but also pave the ground to formalize different forms of resilient responses. In particular, we show that decomposing the network’s operational structure into dynamically decoupled modules allows to formalize what is the impact of a perturbation and to what extent any potential compensation to that perturbation will be successful. We illustrate our approach with a toy model of a farm that operates in a sustainable way producing milk, eggs, and/or grains from other resources. With the help of simulations, we analyze the different types of perturbations and responses that the farm can undergo and how that affects its sustainable operation.

Assessment of the Disaster Resilience of Complex Systems: The Case of the Flood Resilience of a Densely Populated City

In the last decades, resilience became officially the worldwide cornerstone to reduce the risk of disasters and improve preparedness, response, and recovery capacities. Although the concept of resilience is now clear, it is still under debate how to model and quantify it. The aim of this work was to quantify the resilience of a complex system, such as a densely populated and urbanized area, by modelling it with a graph, the mathematical representation of the system element and connections. We showed that the graph can account for the resilience characteristics included in its definition according to the United Nations General Assembly, considering two significant aspects of this definition in particular: (1) resilience is a property of a system and not of single entities and (2) resilience is a property of the system dynamic response. We proposed to represent the exposed elements of the system and their connections (i.e., the services they exchange) with a weighted and redundant graph. By mean of it, we assessed the systemic properties, such as authority and hub values and highlighted the centrality of some elements. Furthermore, we showed that after an external perturbation, such as a hazardous event, each element can dynamically adapt, and a new graph configuration is set up, taking advantage of the redundancy of the connections and the capacity of each element to supply lost services. Finally, we proposed a quantitative metric for resilience as the actual reduction of the impacts of events at different return periods when resilient properties of the system are activated. To illustrate step by step the proposed methodology and show its practical feasibility, we applied it to a pilot study: the city of Monza, a densely populated urban environment exposed to river and pluvial floods.

Estimating resilience in complex systems

Ecology Resilience is an important concept in the study of critical transitions and tipping points in complex systems and is defined by the size of the disturbance that a system can endure before tipping into an alternative stable state. Nevertheless, resilience has proved resistant to measurement. Arani et al. show how the mathematical concept of mean exit time, the time it takes for a system to cross a threshold, can help to solve this problem and characterize the resilience of complex systems. They derived a model approach to estimate exit time from time series data and applied it to examples from a grazed plant population model, lake cyanobacterial data, and Pleistocene-Holocene climate data. This approach may improve our understanding of the dynamical properties of complex systems under threat. Science , aay4895, this issue p. [eaay4895][1] [1]: /lookup/doi/10.1126/science.aay4895

Couplages de résonance symbiotique et hétéro-organisation comme principes fondateurs des systèmes complexes : Entre efficacité dissipative et résilience

Today it is possible to finally go beyond the limits of the analytical paradigm by enriching it with a real systemic dimension allowing a complete integration of the most fundamental recent scientific achievements reflecting the emergence and resilience of complex systems, in particular the so-called "living" states of matter. This contribution proposes to show how the integration of this systemic dimension makes it possible in particular to better understand and manage in a truly lucid and operational way the biological and ecological organizational systems but also socio-economic, even political as, for example, in terms of energy transitions in the face of climate change.Work on thermodynamics of far-from-equilibrium systems has indeed thrown unprecedented light on the understanding of the dynamics of "complex" systems, particularly molecular ones. It is now well established that the emergence of such dynamic organizational structures is determined by maximizing their dissipative efficiency. This promotes the evolution of the system within which it emerges towards a state of maximum uniformity (or entropy) described by the 2nd principle of thermodynamics. These topologically localized states resulting from symbiotic and "hetero-organized" coupling processes between distinct components producing these "dissipative resonance" states are observed from the tropical cyclone to the most sophisticated bio-socio-economic systems It is indeed possible on this basis to establish the symbiotic nature of the processes that determine at all levels the organization and evolution of living states of molecular matter.This was manifested in particular by the emergence at the organo-biological level of hetero-organized and “localized” couplings between nucleic acids and amino acids, the latter giving rise to the first living cells consuming - and therefore dissipating - energy. Endo-symbiosis with certain primitive single-celled organisms with a particular capacity for energy capture and dissipation, such as chloroplasts and mitochondria, other hetero-organization processes, then opened the way for the emergence of co-determined multicellular structures even more effective and resilient on the dissipative front. The process of segmentation (and not of simple division) of an "initial" cell (the "egg") illustrates this symbiotic co-determination between epigenetic components (the "egg white") and genetics (its nucleus) opening the path to the emergence of the potential for tissue differentiation, including its neurological dimension. These processes explain the absence of an absolute hierarchy in the hetero-organization processes and their “probabilistic” component, a bit like in a jazz ensemble each musician can "improvise" (epigenetically) but by constantly agreeing on the others in the interpretation of a specific (genetic) "composition".

Resilience beyond Formal Structures: A Network Perspective towards the Challenges of an Aging Workforce in the Oil and Gas Industry

Changes in workplace demographics in the oil and gas industry have raised a concern about the risks of a knowledge-loss crisis due to mass retirement. The industry response has often consisted of strategies aimed at mapping knowledge across organizational units, codifying knowledge in databases, and mentoring new staff. However, such common managerial responses show important limitations in terms of grasping tacit and network-based dimensions of knowledge in complex oil production operations. Therefore, there is an industrial need for innovative knowledge management practices. In this conceptual article, we look at the knowledge-loss crisis from the perspective of network resilience in complex systems. A central assumption here is that it is important to look at retiring staff not only in terms of their explicit knowledge, but also in relation to their roles in evolving networks of interactions. Why do some social systems adapt to the departure of some individuals, recover from eventual knowledge-loss crises, and keep performing its functions? From an anticipatory logic, network analysis may show the initial conditions of a system and identify possible loss scenarios. From an adaptive logic, network analysis may inform interventions aimed at facilitating processes of interactions from which new knowledge may emerge and spread. Integrated operations may be a step in this direction.

Response to: Comment on “Resilience of Complex Systems: State of the Art and Directions for Future Research”

Response to: Comment on “Resilience of Complex Systems: State of the Art and Directions for Future Research”

Comment on “Resilience of Complex Systems: State of the Art and Directions for Future Research”

Comment on “Resilience of Complex Systems: State of the Art and Directions for Future Research”

Ocean sprawl facilitates dispersal and connectivity of protected species

Highly connected networks generally improve resilience in complex systems. We present a novel application of this paradigm and investigated the potential for anthropogenic structures in the ocean to enhance connectivity of a protected species threatened by human pressures and climate change. Biophysical dispersal models of a protected coral species simulated potential connectivity between oil and gas installations across the North Sea but also metapopulation outcomes for naturally occurring corals downstream. Network analyses illustrated how just a single generation of virtual larvae released from these installations could create a highly connected anthropogenic system, with larvae becoming competent to settle over a range of natural deep-sea, shelf and fjord coral ecosystems including a marine protected area. These results provide the first study showing that a system of anthropogenic structures can have international conservation significance by creating ecologically connected networks and by acting as stepping stones for cross-border interconnection to natural populations.

Toward adaptive decision support for assessing infrastructure system resilience using hidden performance measures

The understanding of resilience is an emerging topic within the study of risks affecting distributed infrastructure systems. Although recent studies have explored the quantification of system resilience, there has been limited research aimed at understanding the role of multiple performance measures, spatiotemporal heterogeneities, and modeling uncertainties within the assessment of resilience and associated decision-making. Under real-world conditions, there is an increased burden on analysts for translating observed system data (including human and electronic sensor observations) into system performance estimates that may not be directly observable. This paper addresses these issues using a scenario-based risk modeling approach to understand: (1) resilience of complex systems, often in cases of hidden (not readily observable) measures of performance, (2) resilience sensitivity to modeling uncertainties in event and system characteristics, and (3) resilience sensitivity to the measurement of performance across multiple operational perspectives. The methods in this paper integrate uncertainty-driven risk and probabilistic modeling within a multi-state Markov-based approach. This study contributes to the state-of-the-art by developing methodologies for assessing community perceptions of infrastructure system resilience using observable factors and inferring possibly hidden performance measures for facilitating adaptive decision-support. The methods are demonstrated with hypothetical spatiotemporal data across multiple system performance dimensions. The analysis results are useful for infrastructure security analysts, system decision-makers, and the general public.

Resilience of Complex Systems: State of the Art and Directions for Future Research

This paper reviews the state of the art on the resilience of complex systems by embracing different research areas and using bibliometric tools. The aim is to identify the main intellectual communities and leading scholars and to synthesize key knowledge of each research area. We also carry out a comparison across the research areas, aimed at analyzing how resilience is approached in any field, how the topic evolved starting from the ecological field of study, and the level of cross‐fertilization among domains. Our analysis shows that resilience of complex systems is a multidisciplinary concept, which is particularly important in the fields of environmental science, ecology, and engineering. Areas of recent and increasing interest are also operation research, management science, business, and computer science. Except for environmental science and ecology, research is fragmented and carried out by isolated research groups. Integration is not only limited inside each field but also between research areas. In particular, we trace the citation links between different research areas and find a very limited number, revealing a scarce cross‐fertilization among domains. We conclude by providing some directions for future research.

Resilience in Complex Systems: An Agent‐Based Approach

ABSTRACTThis paper presents results from a research project on the behavior of complex systems after they experience disruptive events that impact their performance. As systems become more complex, the probability increases that they will exhibit emergent behavior that could lead to system failures or widespread and prolonged service interruptions. A complex adaptive system (CAS) approach is used to conceptualize a complex network system that has been impacted by disruptions and perturbations. A combination of network analysis and agent‐based modeling is used to measure the performance of the system as it responds to disruptive events and restoration efforts. This system‐level behavior is an emergent property of the complex network and represents system resilience. Various resilience measures are used to quantify system resilience and assess the effectiveness of strategies system owners employ to restore the system. We illustrate our techniques by characterizing a critical infrastructure system network as a CAS, and applying an agent‐based simulation with an adaptive algorithm.

Resilience in Firefighting Emergency Response: Standardization and Resilience in Complex Systems

Abstract: This study presents an analysis concerning the use of standard operating procedures (SOPs) and identifying sources of resilience and brittleness in an emergency response exercise conducted as training for Rio de Janeiro State Fire Department's captains, Brazil. From the audiovisual record of the exercise performed by 35 young officers, it was noticed the partial activation of 13 SOPs relevant to the exercise. Not all steps under each SOP were activated or even used. Some possible reasons are the novelty related to the use of simulation as well as the exercise design. This bias in the SOPs use was somehow compensated by sources of resilience that contributed to the actions outcome. Positive and negative aspects of this relationship between standardization and resilience were observed and described, contributing to a better understanding of the activity analysis of these professionals.

Generic Indicators of Ecological Resilience: Inferring the Chance of a Critical Transition

Ecological resilience is the ability of a system to persist in the face of perturbations. Although resilience has been a highly influential concept, its interpretation has remained largely qualitative. Here we describe an emerging family of methods for quantifying resilience on the basis of observations. A first set of methods is based on the phenomenon of critical slowing down, which implies that recovery upon small perturbations becomes slower as a system approaches a tipping point. Such slowing down can be measured experimentally but may also be indirectly inferred from changes in natural fluctuations and spatial patterns. A second group of methods aims to characterize the resilience of alternative states in probabilistic terms based on large numbers of observations as in long time series or satellite images. These generic approaches to measuring resilience complement the system-specific knowledge needed to infer the effects of environmental change on the resilience of complex systems.

Collective work and resilience of complex systems

This article aims to describe the characteristics of collective working situations in complex systems – especially those in nuclear power plants – related to common forms of cooperation, in order to improve systems resilience. In addition, we will try to detail some aspects of collective working situations, emphasizing the differences between various forms of control. The similarities between work activities (multi-addressed messages, linkage to regulation, central and peripheral information) are nonetheless exposed. We conclude by proposing a contribution to support systems design, thus facilitating cooperation in teamwork activities.