390 research outputs found

    Pre-processing for Triangulation of Probabilistic Networks

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    The currently most efficient algorithm for inference with a probabilistic network builds upon a triangulation of a network's graph. In this paper, we show that pre-processing can help in finding good triangulations forprobabilistic networks, that is, triangulations with a minimal maximum clique size. We provide a set of rules for stepwise reducing a graph, without losing optimality. This reduction allows us to solve the triangulation problem on a smaller graph. From the smaller graph's triangulation, a triangulation of the original graph is obtained by reversing the reduction steps. Our experimental results show that the graphs of some well-known real-life probabilistic networks can be triangulated optimally just by preprocessing; for other networks, huge reductions in their graph's size are obtained.Comment: Appears in Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI2001

    Monotonicity in Bayesian Networks

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    For many real-life Bayesian networks, common knowledge dictates that the output established for the main variable of interest increases with higher values for the observable variables. We define two concepts of monotonicity to capture this type of knowledge. We say that a network is isotone in distribution if the probability distribution computed for the output variable given specific observations is stochastically dominated by any such distribution given higher-ordered observations; a network is isotone in mode if a probability distribution given higher observations has a higher mode. We show that establishing whether a network exhibits any of these properties of monotonicity is coNPPP-complete in general, and remains coNP-complete for polytrees. We present an approximate algorithm for deciding whether a network is monotone in distribution and illustrate its application to a real-life network in oncology.Comment: Appears in Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI2004

    A simulation model shows how individual differences affect major life decisions

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    Individuals are faced with a number of major decisions throughout their lives, including the choice of a suitable education, career, and life partner. Making such ‘major life decisions’ is challenging, as is evidenced by substantial rates of divorce and drop-out from higher education. Although poor major life decisions can lead to considerable costs for both individuals and society, little is known about how people make these decisions. This is because major life decisions are not simple short-term weighings of options – they are strongly intertwined with identity development. Here, we present a simulation model of major life decisions that integrates the short-term perspective of decision science with the long-term perspective of identity theory. We model major life decisions as a process comprising many explorations of available options, resulting in changing commitments, and eventually leading to a decision. Using our model, we run a large-scale in silico experiment, systematically simulating how three key individual characteristics affect the choice process and the quality of the decision: (1) exploration tendency (broad vs in-depth), (2) accuracy in assessing how well options fit, and (3) selectiveness. We identify the types of individuals who are at risk of exhibiting ‘maladaptive’ decision dynamics, including ruminative exploration and rash decision making, and conclude that these features often, but not always, lead to bad decisions. Our simulation results generate concrete predictions that can be empirically tested and may eventually result in individually tailored tools to aid individuals in making major life decisions

    Determinants of victimization in patients with severe mental illness:Results from a nation-wide cross-sectional survey in the Netherlands

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    We aimed to examine determinants of criminal victimization (i.e. both personal and property crime victimization) in outpatients with severe mental illness. Data was collected using a multisite epidemiological survey including a random sample of 956 adult outpatients with SMI. Data on 12-month victimization prevalence and frequency were obtained using the victimization scale of the Dutch Crime and Victimization Survey. Demographic characteristics, clinical diagnosis, psychosocial functioning, drug use and alcohol abuse over the past 12 months, co-morbid PTSD diagnosis, physical abuse, physical neglect and sexual abuse in childhood, perpetration of violence over the past 12-months, and anger disposition were assessed as determinants. Univariable and multivariable hurdle regression analyses were conducted to test associations of the potential determinants with victimization prevalence and frequency. We found that different sets of demographic and clinical characteristics were associated with personal and property crime victimization. Clinical characteristics were more pronounced regarding personal crime victimization. In the multivariable model, presence of psychotic disorder, drug use, childhood physical and sexual abuse, and recent violent perpetration were associated with the 12-month prevalence or frequency rate of personal crime victimization. Native Dutch and divorced patients were more at risk as well. Next to this being employed, poor social functioning, having perpetrated a violent crime, as well as alcohol abuse and recent drug use were all significantly related to property crime prevalence or frequency rate in the multivariable model.<br/

    Omnivorousness in sport: The importance of social capital and networks

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    There has been for some time a significant and growing body of research around the relationship between sport and social capital. Similarly, within sociology there has been a corpus of work that has acknowledged the emergence of the omnivore–univore relationship. Surprisingly, relatively few studies examining sport and social capital have taken the omnivore–univore framework as a basis for understanding the relationship between sport and social capital. This gap in the sociology of sport literature and knowledge is rectified by this study that takes not Putnam, Coleman or Bourdieu, but Lin’s social network approach to social capital. The implications of this article are that researchers investigating sport and social capital need to understand more about how social networks and places for sport work to create social capital and, in particular, influence participating in sporting activities. The results indicate that social networks both facilitate and constrain sports participation; whilst family and friendship networks are central in active lifestyles, those who are less active have limited networks

    UP's: A cohort study on recovery in psychotic disorder patients : Design protocol

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    Recovery is a multidimensional concept, including symptomatic, functional, social, as well as personal recovery. The present study aims at exploring psychosocial and biological determinants of personal recovery, and disentangling time-dependent relationships between personal recovery and the other domains of recovery in a sample of people with a psychotic disorder. A cohort study is conducted with a 10-year follow-up. Personal recovery is assessed using the Recovering Quality of Life Questionnaire (ReQoL) and the Individual Recovery Outcomes Counter (I.ROC). Other domains of recovery are assessed by the Positive and Negative Symptom Scale Remission (PANSS-R), the BRIEF-A and the Social Role Participation Questionnaire—Short version (SRPQ) to assess symptomatic, functional and societal recovery, respectively. In addition, multiple biological, psychological, and social determinants are assessed. This study aims to assess the course of personal recovery, and to find determinants and time-dependent relationships with symptomatic, functional and societal recovery in people with a psychotic disorder. Strengths of the study are the large number of participants, long duration of follow-up, multiple assessments over time, extending beyond the treatment trajectory, and the use of a broad range of biological, psychological, and social determinants
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