ISIPTA'07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications

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Estimating the family bias to autism: a bayesian approach

Autism is an age- and sex-related lifelong neurodevelopmental condition characterized pri marily by persistent deficits in core domains such as social communication. It is estimated that ≈ 2% of children have some ASD trait. The autism etiology is mainly due to inherited genetic factors (>80%). The importance of early diagnosis and interventions motivated several studies involving groups at high risk for ASD, those with a greater predisposition to the disorder. Such studies are characterized by evaluating some characteristics of the individual itself or the family members of diagnosed individuals, mainly aiming to predict a future diagnosis or recurrence rates. One of the primary goals of Artificial Intelligence is to create artificial agents capable of intelligent behaviors, such as prediction problems. Prediction problems usually involve reasoning with uncertainty due to some information deficiency, in which the data may be imprecise or incorrect. Such solutions may seek the application of probabilistic methods to construct inference models. In this thesis, we will discuss the development of probabilistic networks capable of estimating the risk of autism among the family members given some evidence (e.g., other family members with ASD). In particular, the main novel contributions of this thesis are as follows: the proposal of some estimates regarding parents with ASD generating children with ASD; the highlight ing regarding the decrease in the ASD prevalence sex ratio among males and females when genetic factors are taken into account; the corroboration and quantification of past evidence that the clustering of ASD in families is primarily due to genetic factors; the computation of some estimates regarding the risk of ASD for parents, grandparents, and siblings; an estimate regarding the number of ASD cases in a family sufficient to attribute the ASD occurrences to the genetic inheritance; the assessment of some estimates for males and females individuals given evidence in grandparents, aunts-or-uncles, nieces-or nephews and cousins; and the proposition of some estimates indicating risk ranges for ASD by genetic similarity

Essays on Beliefs and Economic Behavior

Next to preferences over outcomes, people's subjective beliefs about unobserved states of the world are the central building block of economic models of decision-making. This thesis submits that a more nuanced account of the nature of subjective beliefs can improve the explanatory power of models of economic behavior. It revolves around the following questions. How do people incorporate new information into their beliefs? What are the cognitive mechanisms underlying different updating rules? To what extent is observed heterogeneity in beliefs and behavior predictable? Are beliefs shaped by people's individual experience? How do beliefs translate into economic behavior? The unifying approach of this work is cross-disciplinary, leveraging ideas from other fields such as cognitive science and psychology. The empirical motivation for Chapter 2: "Inattentive Inference" is the pervasive evidence for miscalibration to news in practice. In many situations, beliefs overreact, as if base rates are neglected or new information overweighted, and they often underreact, leading to information rigidities or conservatism in updating. Whether and how these conflicting updating patterns can be reconciled remains an open question. Chapter 2 builds on the observation that most information structures pose a signal extraction problem for belief updating: an agent wants to learn an unobserved state of the world X, but information about X is "compound" in that it also depends on other states Y. Inattention to other causes Y in the signal structure could create misattribution to X. A series of laboratory and online experiments show that most people do not take into account other causes (labelled feature neglect), leading to excessively sensitive and overprecise beliefs. There is pronounced heterogeneity, with up to 90% of beliefs corresponding to three updating rules: feature neglect, Bayesian updating and non-updates. Exploring the underlying mechanism, I find that unawareness about the necessity to factor in alternative causes drives feature neglect, whereas non-updating follows cost-benefit considerations. I propose a conceptual framework that accounts for the combined evidence. Moreover, learning is found to be limited by unawareness, but cues and hints debias by changing people's mental models directly. Chapter 3: "Heterogeneity of Loss Aversion and Expectations-Based Reference Points" examines how people's forward-looking beliefs, i.e., expectations, affect their decisions. A seminal insight from psychology is that we tend to evaluate outcomes relative to a reference point. In theories of reference-dependent decision-making, people code outcomes as gains or losses relative to some reference point. Yet, the location of this reference point is a critical degree of freedom. A recent theoretical advance characterizes the reference point based on people's expectations about their own future outcomes. In the past decade, empirical tests of this model yielded mixed results and there remains a lack of consensus on the location – and thus the empirical relevance – of reference points. Chapter 3 attempts to reconcile different approaches and findings. In this study that is joint work with Lorenz Goette, Charles Sprenger and Alexandre Kellogg, we developed a tightly controlled exchange experiment with two main innovations: First, the design recognizes that testing the role of expectations-based reference points requires experimental control of other plausible avenues of reference dependence, such as the status quo or personal experience. Second, it accommodates a critical confound related to the key behavioral parameter, loss aversion. Loss aversion captures that people dislike losses more than equal-sized gains. A growing body of evidence documents substantial heterogeneity in measured levels of loss aversion, with a substantial fraction of people being loss-neutral or even loss-loving. Different levels of loss aversion, however, lead to different signs of comparative statics. In our results, recognizing heterogeneity in loss aversion allowed us to reliably recover the central prediction of expectations-based reference points. Chapter 4: "Breaking Trust: On the Persistent Effect of Economic Crisis Experience" shifts the focus to a particularly important belief for economic transactions. Trust is the degree of belief in the benevolent intentions of another person. In the realm of economic behavior, trust plays a central role as a prerequisite for all forms of economic exchange: without a minimal amount of trust in the counterpart, no person would be willing to sign a contract. In fact, trust has been shown to affect economic outcomes at the individual, group and societal levels. However, much less is known about the origins of trust. Recent evidence documents that levels of trust vary substantially across locations and over time, but the determinants of this geographical and temporal variation are not well understood. In Chapter 4, which is joint work with Tom Zimmermann, we analyzed the economic implications of a breach of trust argument, positing that trust is not easily restored once it has been abused. Building on a nascent literature on the economic implications of people's lifetime experience, we hypothesized that trust is partially determined by the experience of catastrophic macroeconomic events. Using a variety of identification strategies in a large cross-country sample, we estimated a persistent and robust negative long-term effect of economic crisis experience on trust in other people. In line with the breach of trust hypothesis, the effect was specific to living through crises in trust- intensive domains, most of all banking crises. The effect was not driven by distrust in financial institutions but was accommodated by a lack of confidence in the political class, and operated via beliefs rather than changes in preferences. Chapter 5: "Negative Long-run Effects of Prosocial Behavior on Happiness" studies happiness. In recent times, measures of subjective well-being are increasingly viewed as relevant indicators of a society's welfare, and a rising number of countries have incorporated national happiness levels as a policy objective. This development concurs with a renewed scientific interest in the causes of happiness. Most prominently, recent studies contribute to a debate spanning more than two millennia on the hypothesis that prosocial behavior is a key to happiness. The existing causal evidence indeed confirms a positive influence of prosocial behavior on happiness, but is limited to the short-term effects of an enforced prosocial or selfish act. In Chapter 5, which is joint work with Armin Falk, we reconsider this hypothesis in a behavioral experiment that extends the scope of previous studies in various dimensions. In our Saving a Life paradigm, every participant either saved one human life in expectation or received one hundred euros, respectively. Using a choice between two binary lotteries with different chances of saving a life, we observed subjects' intentions at the same time as creating random variation in prosocial outcomes. We repeatedly measured happiness at different time horizons after the experiment. We confirmed the previous consensus finding of a positive short-term effect, but this effect quickly faded. As time passed, the sign of the effect even reversed, and we recorded significantly greater happiness associated with the selfish outcome than with the prosocial outcome one month later. Our findings hint at distinct sources of happiness as time passes. Chapter 5 provides a first piece of evidence that a comprehensive understanding of the effects of prosocial behavior on happiness requires a more nuanced view that accounts for delayed effects

On the Formation and Economic Implications of Subjective Beliefs and Individual Preferences

The conceptual framework of neoclassical economics posits that individual decision-making processes can be represented as maximization of some objective function. In this framework, people's goals and desires are expressed through the means of preferences over outcomes; in addition, in choosing according to these objectives, people employ subjective beliefs about the likelihood of unknown states of the world. For instance, in the subjective expected utility paradigm, people linearly combine their probabilistic beliefs and preferences over outcomes to form an expected utility function. Much of the parsimony and power of theoretical economic analysis stems from the striking generality and simplicity of this framework. At the same time, the crucial importance of preferences and beliefs in our conceptual apparatus in combination with the heterogeneity in choice behavior that is observed across many economic contexts raises a number of empirical questions. For example, how much heterogeneity do we observe in core preference or belief dimensions that are relevant for a broad range of economic behaviors? If such preferences and beliefs exhibit heterogeneity, then what are the origins of this heterogeneity? How do beliefs and preferences form to begin with? And how does variation in beliefs and preferences translate into economically important heterogeneity in choice behavior? This thesis is organized around these broad questions and hence seeks to contribute to the goal of providing an improved empirical understanding of the foundations and economic implications of individual decision-making processes. The content of this work reflects the deep belief that understanding and conceptualizing decision-making requires economists to embrace ideas from a broad range of fields. Accordingly, this thesis draws insights and techniques from the literatures on behavioral and experimental economics, cultural economics, household finance, comparative development, cognitive psychology, and anthropology. Chapters 1 through 3 combine methods from experimental economics, household finance, and cognitive psychology to investigate the effects of bounded rationality on the formation and explanatory power of subjective beliefs. Chapters 4 through 6 use tools from cultural economics, anthropology, and comparative development to study the cross-country variation in economic preferences as well as its origins and implications. The formation of beliefs about payoff-relevant states of the world crucially hinges on an adequate processing of incoming information. However, oftentimes, the information people receive is rather complex in nature. Chapters 1 and 2 investigate how boundedly rational people form beliefs when their information is subject to sampling biases, i.e., when the information pieces people receive are either not mutually independent or systematically selected. Chapter 1 is motivated by Akerlof and Shiller's popular narrative that from time to time some individuals or even entire markets undergo excessive belief swings, which refers to the idea that sometimes people are overly optimistic and sometimes overly pessimistic over, say, the future development of the stock market. In particular, Akerlof and Shiller argue that such "exuberance" or excessive pessimism might be driven by the pervasive "telling and re-telling of stories". In fact, many real information structures such as the news media generate correlated rather than mutually independent signals, and hence give rise to severe double-counting problems. However, clean evidence on how people form beliefs in correlated information environments is missing. Chapter 1, which is joint work with Florian Zimmermann, provides clean experimental evidence that many people neglect such double-counting problems in the updating process, so that beliefs are excessively sensitive to well-connected information sources and follow an overshooting pattern. In addition, in an experimental asset market, correlation neglect not only drives overoptimism and overpessimism at the individual level, but also gives rise to a predictable pattern of over- and underpricing. Finally, investigating the mechanisms underlying the strong heterogeneity in the presence of the bias, a series of treatment manipulations reveals that many people struggle with identifying double-counting problems in the first place, so that exogenous shifts in subjects' focus have large effects on beliefs. Chapter 2 takes as starting point the big public debate about increased political polarization in the United States, which refers to the fact that political beliefs tend to drift apart over time across social and political groups. Popular narratives by, e.g., Sunstein, Bishop, and Pariser posit that such polarization is driven by people selecting into environments in which they are predominantly exposed to information that confirms their prior beliefs. This pattern introduces a selection problem into the belief formation process, which may result in polarization if people failed to take the non-representativeness among their signals into account. However, again, we do not have meaningful evidence on how people actually form beliefs in such "homophilous" environments. Thus, Chapter 2 shows experimentally that many people do not take into account how their own prior decisions shape their informational environment, but rather largely base their views on their local information sample. In consequence, beliefs excessively depend on people's priors and tend to be too extreme, akin to the concerns about "echo chambers" driving irrational belief polarization across social groups. Strikingly, the distribution of individuals' naivete follows a pronounced bimodal structure - people either fully account for the selection problem or do not adjust for it at all. Allowing for interaction between these heterogeneous updating types induces little learning: neither the endogenous acquisition of advice nor exogenously induced dissent lead to a convergence of beliefs across types, suggesting that the belief heterogeneity induced by selected information may persist over time. Finally, the paper provides evidence that selection neglect is conceptually closely related to correlation neglect in that both cognitive biases appear to be driven by selective attentional patterns. Taken together, chapters 1 and 2 show that many people struggle with processing information that is subject to sampling issues. What is more, the chapters also show that these biases might share common cognitive foundations, hence providing hope for a unified attention-based theory of boundedly rational belief formation. While laboratory experimental techniques are a great tool to study the formation of beliefs, they cannot shed light on the relationship between beliefs and economically important choices. In essentially all economic models, beliefs mechanically map into choice behavior. However, it is not evident that people's beliefs play the same role in generating observed behavior across heterogeneous individuals: while some people's decision process might be well-approximated by the belief and preference-driven choice rules envisioned by economic models, other people might use, e.g., simple rules of thumb instead, implying that their beliefs should be largely irrelevant for their choices. That is, bounded rationality might not only affect the formation of beliefs, but also the mapping from beliefs to choices. In Chapter 3, Tilman Drerup, Hans-Martin von Gaudecker, and I take up this conjecture in the context of measurement error problems in household finance: while subjective expectations are important primitives in models of portfolio choice, their direct measurement often yields imprecise and inconsistent measures, which is typically treated as a pure measurement error problem. In contrast to this perspective, we argue that individual-level variation in the precision of subjective expectations measures can actually be productively exploited to gain insights into whether economic models of portfolio choice provide an adequate representation of individual decision processes. Using a novel dataset on experimentally measured subjective stock market expectations and real stock market decisions collected from a large probability sample of the Dutch population, we estimate a semiparametric double index model to explore this conjecture. Our results show that investment decisions exhibit little variation in economic model primitives when individuals provide error-ridden belief statements. In contrast, they predict strong variation in investment decisions for individuals who report precise expectation measures. These findings indicate that the degree of precision in expectations data provides useful information to uncover heterogeneity in choice behavior, and that boundedly rational beliefs need not necessarily map into irrational choices. In the standard neoclassical framework, people's beliefs only serve the purpose of achieving a given set of goals. In many applications of economic interest, these goals are well-characterized by a small set of preferences, i.e., risk aversion, patience, and social preferences. Prior research has shown that these preferences vary systematically in the population, and that they are broadly predictive of those behaviors economic theory supposes them to. At the same time, this empirical evidence stems from often fairly special samples in a given country, hence precluding an analysis of how general the variation and predictive power in preferences is across cultural, economic, and institutional backgrounds. In addition, it is conceivable that preferences vary not just at an individual level, but also across entire populations - if so, what are the deep historical or cultural origins of this variation, and what are its (aggregate) economic implications? Chapters 4 through 6 take up these questions by presenting and analyzing the Global Preference Survey (GPS), a novel globally representative dataset on risk and time preferences, positive and negative reciprocity, altruism, and trust for 80,000 individuals, drawn as representative samples from 76 countries around the world, representing 90 percent of both the world's population and global income. In joint work with Armin Falk, Anke Becker, Thomas Dohmen, David Huffman, and Uwe Sunde, Chapter 4 presents the GPS data and shows that the global distribution of preferences exhibits substantial variation across countries, which is partly systematic: certain preferences appear in combination, and follow distinct economic, institutional, and geographic patterns. The heterogeneity in preferences across individuals is even more pronounced and varies systematically with age, gender, and cognitive ability. Around the world, the preference measures are predictive of a wide range of individual-level behaviors including savings and schooling decisions, labor market and health choices, prosocial behaviors, and family structure. We also shed light on the cultural origins of preference variation around the globe using data on language structure. The magnitude of the cross-country variation in preferences is striking and raises the immediate question of what brought it about. Chapter 5 presents joint work with Anke Becker and Armin Falk in which we use the GPS to show that the migratory movements of our early ancestors thousands of years ago have left a footprint in the contemporary cross-country distributions of preferences over risk and social interactions. Across a wide range of regression specifications, differences in preferences between populations are significantly increasing in the length of time elapsed since the respective groups shared common ancestors. This result obtains for risk aversion, altruism, positive reciprocity, and trust, and holds for various proxies for the structure and timing of historical population breakups, including genetic and linguistic data or predicted measures of migratory distance. In addition, country-level preference endowments are non-linearly associated with migratory distance from East Africa, i.e., genetic diversity. In combination with the relationships between language structure and preferences established in Chapter 4, these results point to the importance of very long-run events for understanding the global distribution of some of the key economic traits. Given these findings on the very deep roots of the cross-country variation in preferences, an interesting - and conceptually different - question is whether such country-level preference profiles might have systematic aggregate economic implications. Indeed, according to standard dynamic choice theories, patience is a key driving factor behind the accumulation of productive resources and hence ultimately of income not just at an individual, but also at a macroeconomic level. Using the GPS data on patience, Chapter 6 (joint work with Thomas Dohmen, Armin Falk, David Huffman, and Uwe Sunde) investigates the empirical relevance of this hypothesis in the context of a micro-founded development framework. Around the world, patient people invest more into human and physical capital and have higher incomes. At the macroeconomic level, we establish a significant reduced-form relationship between patience and contemporary income as well as medium- and long-run growth rates, with patience explaining a substantial fraction of development differences across countries and subnational regions. In line with a conceptual framework in which patience drives income through the accumulation of productive resources, average patience also strongly correlates with aggregate human and physical capital accumulation as well as investments into productivity. Taken together, this thesis has a number of unifying themes and insights. First, consistent with the vast heterogeneity in observed choices, people exhibit a large amount of variation in beliefs and preferences, and in how they combine these into choice rules. Second, at least part of this heterogeneity is systematic and has identifyable sources: preferences over risk, time, and social interactions appear to have very deep historical or cultural origins, but also systematically vary with individual characteristics; belief heterogeneity, on the other hand, is partly driven by bounded rationality and its systematic, predictable effects on information-processing. Third, and finally, this heterogeneity in beliefs and preferences is likely to have real economic implications: across cultural and institutional backgrounds, preferences correlate with the types of behaviors that economic models envision them to, not just across individuals, but also at the macroeconomic level; subjective beliefs are predictive of behavior, too, albeit with the twist that certain subgroups of the population do not appear to entertain stable belief distributions to begin with. In sum, (I believe that) much insight is to be gained from further exploring these fascinating topics

Economics of primary caries prevention in preschool children

Background: Childhood caries continues to be a pandemic disease and a significant but preventable public health problem worldwide. Caries can have a major impact on children's health and quality of life as well as represent cost to individuals, the health sector and society. Research indicates that children who develop caries in early childhood are likely to have a high risk of the disease in adolescence and adulthood. Dental caries is a preventable disease and currently a range of nationwide programmes, community-based programmes and clinical strategies exist to reduce caries prevalence in children. Notwithstanding the fact that childhood caries is very widespread and that it poses a substantial economic burden, there is a paucity of economic evaluations of caries prevention interventions in preschoolers. The lack of high-quality economic evaluations makes it difficult for decision-makers to determine which interventions to provide within the remit of health services and local authorities. Aim: To explore the role of economic evaluation in primary caries prevention in preschool children aged 2-5 years. This aim was met through answering the following three research questions. (1) What is the existing evidence in the field of economic evaluation of primary caries prevention in children aged 2-5 years? (2) Which general health and oral health-related quality of life measures have been used in 3-5-year-old populations? And which of these measures are best suited to be used in a caries prevention randomised controlled trial for this age group? (3) Is the application of fluoride varnish delivered in nursery settings in addition to the other usual components of the Scottish child oral health improvement programme, Childsmile, (treatment as usual) cost-effective in comparison with treatment as usual only? Methods: Three interlinked empirical work segments were undertaken to address these research questions. (1) A systematic review of economic evaluations of primary caries prevention in 2-5-year-old preschool children. (2) A non-systematic review of instruments for measuring general and oral health-related quality of life in 3-5-year-old children. (3) An economic evaluation of the Protecting Teeth @ 3 randomised controlled trial (trial registration: EUDRACT: 2012-002287-26; ClinicalTrials.gov: NCT01674933). Results: (1) The systematic review of economic evaluations of primary caries prevention in 2-5-year-olds found that cost analysis and cost-effectiveness analysis were the most frequently used types of economic evaluations. Only one study employed cost-utility analysis. The systematic review highlighted wide variation in: (a) types of caries prevention interventions investigated; (b) effectiveness measures used; (c) how costs and outcomes are reported; and d) study perspective (when indicated). The parameters not reported well included study perspective, baseline year, sensitivity analysis, and discount rate. The results of the quality assessment of the full economic evaluations using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist showed substantial variation in reporting quality. The CHEERS items that were most often unmet were characterizing uncertainty, study perspective, study parameters, and estimating resources and costs. (2) The review of general health and oral health-related quality of life measures identified a range of existing questionnaires for use in preschool populations (age 3-5 years) and their strengths and limitations were considered. Only two preference-based general health-related quality of life instruments that had been used in 3-5-year-olds were identified. No preference-based oral health-related quality of life measures for preschoolers were identified. Four instruments were selected to be used in the Protecting Teeth @ 3 trial: the Child Health Utility 9 Dimensions, PedsQL (Paediatric Quality of Life Inventory) Core, PedsQL Oral Health (an oral health specific add-on to PedsQL Core) and the Scale of Oral Health Outcomes for 5-year-old children. (3) The findings of the Protecting Teeth @ 3 trial economic evaluation demonstrated that there were no statistically significant differences in total costs, quality adjusted life years (QALYs) accumulated, the change in the clinical effectiveness outcome (d3mft), and in general health and oral health-related quality of life measures at 24 months between the intervention and control groups. The mean difference in total costs between the fluoride varnish (intervention) and treatment as usual (control) group was £68 (p=0.382; 95% confidence interval £18, £144). The mean difference in QALYs was -0.004 (p= 0.636; 95% confidence interval -0.016, 0.007). The probability that the fluoride varnish intervention was cost-effective at the £20,000 threshold was 11%. Conclusions: The systematic review of economic evaluations of primary caries prevention in 2-5-year-olds found that within the past two decades, there has been an increase in the number of economic evaluations of caries prevention interventions in preschool children. However, there was inconsistency in how these economic evaluations of primary caries prevention were conducted and reported. Lack of use of preference-based health-related quality-of-life measures was identified. The use of appropriate study methodologies and greater attention to recommended economic evaluations design are required to further improve quality. Due to small numbers of studies investigating each intervention type (for example, fluoride varnish, oral health education, dental sealants, toothbrushing, water fluoridation) and the questionable methodological quality of many of the reviewed economic evaluations, it was not possible to arrive at reliable conclusions with regards to the economic value of primary caries prevention. With dental caries being one of the most common diseases affecting humans worldwide, the identification of cost-effective prevention strategies in children should be a global public health priority. In order for this to be achieved, studies should be designed to include economic evaluations using best practice methods guidance and adhering to standards for reporting and presenting. The review of general health and oral health-related quality of life measures used in 3-5-year-olds identified a range of existing questionnaires for use in preschool populations – both for parental proxy reporting and child self-reporting. Four instruments were selected to be used in the Protecting Teeth @ 3 trial. Further research and development of new preference-based measures suitable for preschoolers (or their parents/guardians as a proxy) are required. The results of the economic evaluation of the Protecting Teeth @ 3 trial show that applying fluoride varnish in nursery settings in addition to the existing treatment a usual (all other components of the Childsmile programme, apart from nursery fluoride varnish) is not likely to be cost-effective. In view of previously proven clinical effectiveness and economic worthiness of the universal nursery toothbrushing component of Childsmile, which was shown to be highly cost saving, as well as being effective and cost saving in the most deprived populations, continuation of the programme of targeted nursery fluoride varnish in its most recent (pre-COVID-19) form and shape in addition to nursery toothbrushing and other routine Childsmile components needs to be reviewed in consultation with policy makers. The findings also have wider implications for other countries looking to develop their own childhood caries prevention programmes

Talking About Uncertainty

In the first article we review existing theories of uncertainty. We devote particular attention to the relation between metacognition, uncertainty and probabilistic expectations. We also analyse the role of natural language and communication for the emergence and resolution of states of uncertainty. We hypothesize that agents feel uncertainty in relation to their levels of expected surprise, which depends on probabilistic expectations-gaps elicited during communication processes. Under this framework above tolerance levels of expected surprise can be considered informative signals. These signals can be used to coordinate, at the group and social level, processes of revision of probabilistic expectations. When above tolerance levels of uncertainty are explicated by agents through natural language, in communication networks and public information arenas, uncertainty acquires a systemic role of coordinating device for the revision of probabilistic expectations. The second article of this research seeks to empirically demonstrate that we can crowd source and aggregate decentralized signals of uncertainty, i.e. expected surprise, coming from market agents and civil society by using the web and more specifically Twitter as an information source that contains the wisdom of the crowds concerning the degree of uncertainty of targeted communities/groups of agents at a given moment in time. We extract and aggregate these signals to construct a set of civil society uncertainty proxies by country. We model the dependence among our civil society uncertainty indexes and existing policy and market uncertainty proxies, highlighting contagion channels and differences in their reactiveness to real-world events that occurred in the year 2016, like the EU-referendum vote and the US presidential elections. In the third article, we propose a new instrument, called Worldwide Uncertainty Network, to analyse the uncertainty contagion dynamics across time and areas of the world. Such an instrument can be used to identify the systemic importance of countries in terms of their civil society uncertainty social percolation role. Our results show that civil society uncertainty signals coming from the web may be fruitfully used to improve our understanding of uncertainty contagion and amplification mechanisms among countries and between markets, civil society and political systems

Transformation of graphical models to support knowledge transfer

Menschliche Experten verfügen über die Fähigkeit, ihr Entscheidungsverhalten flexibel auf die jeweilige Situation abzustimmen. Diese Fähigkeit zahlt sich insbesondere dann aus, wenn Entscheidungen unter beschränkten Ressourcen wie Zeitrestriktionen getroffen werden müssen. In solchen Situationen ist es besonders vorteilhaft, die Repräsentation des zugrunde liegenden Wissens anpassen und Entscheidungsmodelle auf unterschiedlichen Abstraktionsebenen verwenden zu können. Weiterhin zeichnen sich menschliche Experten durch die Fähigkeit aus, neben unsicheren Informationen auch unscharfe Wahrnehmungen in die Entscheidungsfindung einzubeziehen. Klassische entscheidungstheoretische Modelle basieren auf dem Konzept der Rationalität, wobei in jeder Situation die nutzenmaximale Entscheidung einer Entscheidungsfunktion zugeordnet wird. Neuere graphbasierte Modelle wie Bayes\u27sche Netze oder Entscheidungsnetze machen entscheidungstheoretische Methoden unter dem Aspekt der Modellbildung interessant. Als Hauptnachteil lässt sich die Komplexität nennen, wobei Inferenz in Entscheidungsnetzen NP-hart ist. Zielsetzung dieser Dissertation ist die Transformation entscheidungstheoretischer Modelle in Fuzzy-Regelbasen als Zielsprache. Fuzzy-Regelbasen lassen sich effizient auswerten, eignen sich zur Approximation nichtlinearer funktionaler Beziehungen und garantieren die Interpretierbarkeit des resultierenden Handlungsmodells. Die Übersetzung eines Entscheidungsmodells in eine Fuzzy-Regelbasis wird durch einen neuen Transformationsprozess unterstützt. Ein Agent kann zunächst ein Bayes\u27sches Netz durch Anwendung eines in dieser Arbeit neu vorgestellten parametrisierten Strukturlernalgorithmus generieren lassen. Anschließend lässt sich durch Anwendung von Präferenzlernverfahren und durch Präzisierung der Wahrscheinlichkeitsinformation ein entscheidungstheoretisches Modell erstellen. Ein Transformationsalgorithmus kompiliert daraus eine Regelbasis, wobei ein Approximationsmaß den erwarteten Nutzenverlust als Gütekriterium berechnet. Anhand eines Beispiels zur Zustandsüberwachung einer Rotationsspindel wird die Praxistauglichkeit des Konzeptes gezeigt.Human experts are able to flexible adjust their decision behaviour with regard to the respective situation. This capability pays in situations under limited resources like time restrictions. It is particularly advantageous to adapt the underlying knowledge representation and to make use of decision models at different levels of abstraction. Furthermore human experts have the ability to include uncertain information and vague perceptions in decision making. Classical decision-theoretic models are based directly on the concept of rationality, whereby the decision behaviour prescribed by the principle of maximum expected utility. For each observation some optimal decision function prescribes an action that maximizes expected utility. Modern graph-based methods like Bayesian networks or influence diagrams make use of modelling. One disadvantage of decision-theoretic methods concerns the issue of complexity. Finding an optimal decision might become very expensive. Inference in decision networks is known to be NP-hard. This dissertation aimed at combining the advantages of decision-theoretic models with rule-based systems by transforming a decision-theoretic model into a fuzzy rule-based system. Fuzzy rule bases are an efficient implementation from a computational point of view, they can approximate non-linear functional dependencies and they are also intelligible. There was a need for establishing a new transformation process to generate rule-based representations from decision models, which provide an efficient implementation architecture and represent knowledge in an explicit, intelligible way. At first, an agent can apply the new parameterized structure learning algorithm to identify the structure of the Bayesian network. The use of learning approaches to determine preferences and the specification of probability information subsequently enables to model decision and utility nodes and to generate a consolidated decision-theoretic model. Hence, a transformation process compiled a rule base by measuring the utility loss as approximation measure. The transformation process concept has been successfully applied to the problem of representing condition monitoring results for a rotation spindle

Changing climate, changing decisions : understanding climate adaptation decision-making and the way science supports it

Tese de doutoramento, Ciências do Ambiente, Universidade de Lisboa, Faculdade de Ciências, Universidade Nova de Lisboa, 2015The current pace of global mitigation efforts brings about growing concerns about climate change impacts. In turn, even in developed countries, most societies are often vulnerable to present day climate and will most likely see those vulnerabilities exacerbated by future climate trends and extremes, accentuating the need for a coherent response through adaptation efforts. Such efforts will always have to be developed in face of uncertainty. The deeply rooted uncertainties that underpin climate change adaptation as a scientific, political and societal endeavour will always be a part of adaptation decision-making processes. It is fundamental that decision-makers and scientific communities find common ground that allows to exchange the necessary knowledge on “why to adapt”, but also to develop the required frameworks, methods and tools that sustain a clearer understanding of “what to adapt” and “how to adapt” under long-term, uncertain circumstances. This thesis is about climate adaptation decisions and decision-making processes, and how science supports and equips them to handle uncertainty. The assessment and conclusions presented in this thesis reflect research that was transdisciplinary in nature and that included working close to decision-makers in their real-life contexts. The main objective of this thesis is to enrich the understanding of how adaptation decision-making takes place in those contexts and how science can better support it in dealing with associated uncertainties. Three key research questions underpin this thesis. The first deals with the issue whether transdisciplinarity in adaptation research is a fundamental condition for practical adaptation decision-making. This thesis argues that although transdisciplinarity may be a necessary condition, it is not a sufficient one to assure that “good” or “better” real-life adaptation decisions are made. Participatory, practice-oriented research is of outmost importance, but it has to be complemented by a more fundamental inquiry and concept development from disciplinary sciences and with changes in the operational and/or normative standards associated with long-lasting decisions. Transdisciplinarity has been framed as a potential solution for the gap between knowledge production and practical adaptation action. However, a more fundamental change in the way adaptation decision-making processes are framed, one that goes beyond the simple assimilation of the perceived needs of decision-makers, may be required to bridge that challenge. The second question reflects the current gap in the understanding of what climate adaptation decisions are and how they relate to existing or perceived uncertainties. Using a set of selected case-studies spanning across a wide range of sectors and different real-life decisions, this thesis reviewed and analysed how adaptation decisions are being made in practice, their knowledge requirements, and the implications that dealing with uncertainty has regarding their outcomes. In order to consider all steps of the adaptation decision-making process, interviews were conducted with both decision-makers and those involved in supporting them via science and other activities. Results demonstrate the importance of considering both dimensions and respective contexts in dealing with uncertainty. However, results also suggest that uncertainty-management is not a guarantee of action, and that the current framing of adaptation decision-making is still very much tied to a rational-linear view, both from the policy and decision-making perspective, as in the science and decision-support standpoint. This leads to a third research question that aims to identify if current adaptation decision-making frameworks are well equipped to characterise, support adaptation and enhance adaptation action under uncertainty. In the context of this thesis, a decision-making framework is a holistic set of concepts, perspectives or approaches that support the entire adaptation decisionmaking process. This thesis argues that such frameworks should necessarily include and integrate all dimensions that naturally occur in an adaptation process namely, the decision-objectives, the decision-support, the decision-making and the respective decision-outcomes. Current frameworks have been mostly framed from a research and expert perspective that follows a rational approach to decision-making under uncertainty. Under such perspective, it is assumed that by providing information and decision-support practical adaptation decisions will be made. This appears to be sufficient to deal with strategic decisions that look into improving adaptive capacity, but seems no longer fit-for-purpose when it comes to operational decisions, the type generally required to advance vulnerability-reducing actions.Centre for Ecology, Evolution and Environmental Changes (cE3c, project Climate Change Impacts, Adaptation and Modelling - CCIAM); Wageningen University and Research Centr