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Many adaptive systems sit near a tipping or critical point. For systems near a critical point small changes to component behaviour can induce large-scale changes in aggregate structure and function. Criticality can be adaptive when the environment is changing, but entails reduced robustness through sensitivity. This tradeoff can be resolved

Many adaptive systems sit near a tipping or critical point. For systems near a critical point small changes to component behaviour can induce large-scale changes in aggregate structure and function. Criticality can be adaptive when the environment is changing, but entails reduced robustness through sensitivity. This tradeoff can be resolved when criticality can be tuned. We address the control of finite measures of criticality using data on fight sizes from an animal society model system (Macaca nemestrina, n=48). We find that a heterogeneous, socially organized system, like homogeneous, spatial systems (flocks and schools), sits near a critical point; the contributions individuals make to collective phenomena can be quantified; there is heterogeneity in these contributions; and distance from the critical point (DFC) can be controlled through biologically plausible mechanisms exploiting heterogeneity. We propose two alternative hypotheses for why a system decreases the distance from the critical point.

ContributorsDaniels, Bryan (Author) / Krakauer, David (Author) / Flack, Jessica (Author) / ASU-SFI Center for Biosocial Complex Systems (Contributor)
Created2017-02-10
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Description

We find that the flow of attention on the Web forms a directed, tree-like structure implying the time-sensitive browsing behavior of users. Using the data of a news sharing website, we construct clickstream networks in which nodes are news stories and edges represent the consecutive clicks between two stories. To

We find that the flow of attention on the Web forms a directed, tree-like structure implying the time-sensitive browsing behavior of users. Using the data of a news sharing website, we construct clickstream networks in which nodes are news stories and edges represent the consecutive clicks between two stories. To identify the flow direction of clickstreams, we define the “flow distance” of nodes (Li), which measures the average number of steps a random walker takes to reach the ith node. It is observed that Li is related with the clicks (Ci) to news stories and the age (Ti) of stories. Putting these three variables together help us understand the rise and decay of news stories from a network perspective. We also find that the studied clickstream networks preserve a stable structure over time, leading to the scaling between users and clicks. The universal scaling behavior is confirmed by the 1,000 Web forums. We suggest that the tree-like, stable structure of clickstream networks reveals the time-sensitive preference of users in online browsing. To test our assumption, we discuss three models on individual browsing behavior, and compare the simulation results with empirical data.

ContributorsWang, Cheng-Jun (Author) / Wu, Lingfei (Author) / Zhang, Jiang (Author) / Janssen, Marco (Author) / ASU-SFI Center for Biosocial Complex Systems (Contributor)
Created2016-09-28
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Description

The planetary boundary framework constitutes an opportunity for decision makers to define climate policy through the lens of adaptive governance. Here, we use the DICE model to analyze the set of adaptive climate policies that comply with the two planetary boundaries related to climate change: (1) staying below a CO2…

The planetary boundary framework constitutes an opportunity for decision makers to define climate policy through the lens of adaptive governance. Here, we use the DICE model to analyze the set of adaptive climate policies that comply with the two planetary boundaries related to climate change: (1) staying below a CO2 concentration of 550 ppm until 2100 and (2) returning to 350 ppm in 2100. Our results enable decision makers to assess the following milestones: (1) a minimum of 33% reduction of CO2 emissions by 2055 in order to stay below 550 ppm by 2100 (this milestone goes up to 46% in the case of delayed policies); and (2) carbon neutrality and the effective implementation of innovative geoengineering technologies (10% negative emissions) before 2060 in order to return to 350 ppm in 2100, under the assumption of getting out of the baseline scenario without delay. Finally, we emphasize the need to use adaptive path-based approach instead of single point target for climate policy design.

Created2017-02-07
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Description

Experiments have made important contributions to our understanding of human behavior, including behavior relevant for understanding social-ecological systems. When there is a conflict between individual and group interests in social-ecological systems, social dilemmas occur. From the many types of social-dilemma formulations that are used to study collective action, common-pool resource

Experiments have made important contributions to our understanding of human behavior, including behavior relevant for understanding social-ecological systems. When there is a conflict between individual and group interests in social-ecological systems, social dilemmas occur. From the many types of social-dilemma formulations that are used to study collective action, common-pool resource and public-good dilemmas are most relevant for social-ecological systems. Experimental studies of both common-pool resource and public-good dilemmas have shown that many predictions based on the conventional theory of collective action, which assumes rational, self-interested behavior, do not hold. More cooperation occurs than predicted (Ledyard 1995), “cheap talk” increases cooperation (Ostrom 2006), and participants are willing to invest in sanctioning free riders (Yamagishi 1986, Ostrom et al. 1992, Fehr and Gächter 2000, Chaudhuri 2011). Experiments have also demonstrated a diversity of motivations, which affect individual decisions about cooperation and sanctioning (see Fehr and Fischbacher 2002 and Sobel 2005 for reviews, and Bowles 2008 for policy implications).

Created2015
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Sequential affect dynamics generated during the interaction of intimate dyads, such as married couples, are associated with a cascade of effects - some good and some bad - on each partner, close family members, and other social contacts. Although the effects are well documented, the probabilistic structures associated with micro-social

Sequential affect dynamics generated during the interaction of intimate dyads, such as married couples, are associated with a cascade of effects - some good and some bad - on each partner, close family members, and other social contacts. Although the effects are well documented, the probabilistic structures associated with micro-social processes connected to the varied outcomes remain enigmatic. Using extant data we developed a method of classifying and subsequently generating couple dynamics using a Hierarchical Dirichlet Process Hidden semi-Markov Model (HDP-HSMM). Our findings indicate that several key aspects of existing models of marital interaction are inadequate: affect state emissions and their durations, along with the expected variability differences between distressed and nondistressed couples are present but highly nuanced; and most surprisingly, heterogeneity among highly satisfied couples necessitate that they be divided into subgroups. We review how this unsupervised learning technique generates plausible dyadic sequences that are sensitive to relationship quality and provide a natural mechanism for computational models of behavioral and affective micro-social processes.

ContributorsGriffin, William (Author) / Li, Xun (Author) / ASU-SFI Center for Biosocial Complex Systems (Contributor)
Created2016-05-17
Description
Community-based volunteer organizations are critical to natural resource management in the United States. However, due to volunteer involvement, these organizations struggle with collective action problems: coping with free riding, solving commitment problems, arranging for the supply of new institutions, and monitoring individual compliance with sets of rules. In this study,

Community-based volunteer organizations are critical to natural resource management in the United States. However, due to volunteer involvement, these organizations struggle with collective action problems: coping with free riding, solving commitment problems, arranging for the supply of new institutions, and monitoring individual compliance with sets of rules. In this study, we explore how volunteer organizations can overcome these challenges. To explore how they overcome these challenges, we use the Institutional Analysis and Development framework and the Institutional Design Principles. These frameworks help us understand the impact of natural resource conditions, community attributes, and the rules in use impact volunteer organizations. For this research, we focused on lake organizations in Wisconsin. We collected our data through semi-structured interviews with thirty-one lake organizations and public data. The data were analyzed using constant comparison and linear regression, followed by qualitative comparative analysis (QCA). We reinforce the importance of considering the system holistically when managing a resource the natural resource conditions, the community attributes, and the rules in use. Our study shows the importance of graduated sanctions and low-cost conflict resolution on social-ecological system outcomes. Volunteer-based resource management are an effective way to tailor management strategies to the natural resource condition and the community attributes.
ContributorsWhittaker, Dane (Author) / Janssen, Marco (Contributor) / Janssen,Marco (Contributor) / Leonard, Bryan (Contributor) / Solomon, Chris (Contributor)
Created2020-04-24
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Description

This study extended the findings of Tighe and Schatschneider (2015) by investigating the predictive utility of separate dimensions of morphological awareness as well as vocabulary knowledge to reading comprehension in adult basic education (ABE) students. We competed two- and three-factor structural equation models of reading comprehension. A three-factor model of

This study extended the findings of Tighe and Schatschneider (2015) by investigating the predictive utility of separate dimensions of morphological awareness as well as vocabulary knowledge to reading comprehension in adult basic education (ABE) students. We competed two- and three-factor structural equation models of reading comprehension. A three-factor model of real word morphological awareness, pseudoword morphological awareness, and vocabulary knowledge emerged as the best fit and accounted for 79% of the reading comprehension variance. The results indicated that the constructs contributed jointly to reading comprehension; however, vocabulary knowledge was the only potentially unique predictor (p = 0.052), accounting for an additional 5.6% of the variance. This study demonstrates the feasibility of applying a latent variable modeling approach to examine individual differences in the reading comprehension skills of ABE students. Further, this study replicates the findings of Tighe and Schatschneider (2015) on the importance of differentiating among dimensions of morphological awareness in this population.

Created2016-02-04
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Description

The structure and dynamics of ecosystems can affect the information available to resource users on the state of the common resource and the actions of other resource users. We present results from laboratory experiments that showed that the availability of information about the actions of other participants affected the level

The structure and dynamics of ecosystems can affect the information available to resource users on the state of the common resource and the actions of other resource users. We present results from laboratory experiments that showed that the availability of information about the actions of other participants affected the level of cooperation. Since most participants in commons dilemmas can be classified as conditional cooperators, not having full information about the actions of others may affect their decisions. When participants had more information about others, there was a more rapid reduction of the resource in the first round of the experiment. When communication was allowed, limiting the information available made it harder to develop effective institutional arrangements. When communication was not allowed, there was a more rapid decline of performance in groups where information was limited. In sum, the results suggest that making information available to others can have an important impact on the conditional cooperation and the effectiveness of communication.

Created2013
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Description

Recent advances in nonequilibrium statistical physics have provided unprecedented insight into the thermodynamics of dynamic processes. The author recently used these advances to extend Landauer’s semi-formal reasoning concerning the thermodynamics of bit erasure, to derive the minimal free energy required to implement an arbitrary computation. Here, I extend this analysis,

Recent advances in nonequilibrium statistical physics have provided unprecedented insight into the thermodynamics of dynamic processes. The author recently used these advances to extend Landauer’s semi-formal reasoning concerning the thermodynamics of bit erasure, to derive the minimal free energy required to implement an arbitrary computation. Here, I extend this analysis, deriving the minimal free energy required by an organism to run a given (stochastic) map π from its sensor inputs to its actuator outputs. I use this result to calculate the input-output map π of an organism that optimally trades off the free energy needed to run π with the phenotypic fitness that results from implementing π. I end with a general discussion of the limits imposed on the rate of the terrestrial biosphere’s information processing by the flux of sunlight on the Earth.

Created2016-04-13
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Description
Collaborative research is not only a form of social and human capital and a public good, but also a fundamental elicitor of positive Collective Action. Collaborative Research Networks can serve as models of proactive and purposive Collective Action and catalysts of societal change, if they function as more than hubs

Collaborative research is not only a form of social and human capital and a public good, but also a fundamental elicitor of positive Collective Action. Collaborative Research Networks can serve as models of proactive and purposive Collective Action and catalysts of societal change, if they function as more than hubs of research and knowledge. It is the goal of this Honors Thesis to examine the current nature under which collaborative research networks, focused on matters of Global Health or Sustainability, operate., how they are organized, what type of collaboration they engage in, and who collaborates with whom. A better understanding of these types of networks can lead to the formation of more effective networks that can develop innovative solutions to our collective Global Health and Sustainability problems.
ContributorsHodzic, Mirna (Author) / Van Der Leeuw, Sander (Thesis director) / Janssen, Marco (Committee member) / Schoon, Michael (Committee member) / Barrett, The Honors College (Contributor)
Created2012-05