946 resultados para Decision Theory


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Gibbs, N., Getting Constitutional Theory into Proportion: A Matter of Interpretation?, Oxford Journal of Legal Studies, 27 (1), 175-191. RAE2008

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Using a classic grounded theory methodology (CGT), this study explores the phenomenon of moral shielding within mental health multidisciplinary teams (MDTS). The study was located within three catchment areas engaged in acute mental health service practice. The main concern identified was the maintenance of a sense of personal integrity during situational binds. Through theoretical sampling thirty two practitioners, including; doctors, nurses, social workers, occupational therapists, counsellors and psychologists, where interviewed face to face. In addition, emergent concepts were identified through observation of MDTs in clinical and research practice. Following a classic grounded theory methodology, data collection and analysis occurred simultaneously. A constant comparative approach was adopted and resulted in the immergence of three sub- core categories; moral abdication, moral hinting and pseudo-compliance. Moral abdication seeks to re-position within an event in order to avoid or deflect the initial obligation to act, it is a strategy used to remove or reduce moral ownership. Moral gauging represents the monitoring of an event with the goal of judging the congruence of personal principles and commitments with that of other practitioners. This strategy is enacted in a bid to seek allies for the support of a given moral position. Pseudo-compliance represents behaviour that hides desired principles and commitments in order to shield them from challenge. This strategy portrays agreement with the dominant position within the MDT, whilst holding a contrary position. It seeks to preserve a reservoir of emotional energy required to maintain a sense of personal integrity. Practitioners who were successful in enacting moral shielding were found to not experience significant emotional distress associated with the phenomenon of moral distress; suggesting that these practitioners had found mechanisms to manage situational binds that threatened their sense of personal integrity.

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In many real world situations, we make decisions in the presence of multiple, often conflicting and non-commensurate objectives. The process of optimizing systematically and simultaneously over a set of objective functions is known as multi-objective optimization. In multi-objective optimization, we have a (possibly exponentially large) set of decisions and each decision has a set of alternatives. Each alternative depends on the state of the world, and is evaluated with respect to a number of criteria. In this thesis, we consider the decision making problems in two scenarios. In the first scenario, the current state of the world, under which the decisions are to be made, is known in advance. In the second scenario, the current state of the world is unknown at the time of making decisions. For decision making under certainty, we consider the framework of multiobjective constraint optimization and focus on extending the algorithms to solve these models to the case where there are additional trade-offs. We focus especially on branch-and-bound algorithms that use a mini-buckets algorithm for generating the upper bound at each node of the search tree (in the context of maximizing values of objectives). Since the size of the guiding upper bound sets can become very large during the search, we introduce efficient methods for reducing these sets, yet still maintaining the upper bound property. We define a formalism for imprecise trade-offs, which allows the decision maker during the elicitation stage, to specify a preference for one multi-objective utility vector over another, and use such preferences to infer other preferences. The induced preference relation then is used to eliminate the dominated utility vectors during the computation. For testing the dominance between multi-objective utility vectors, we present three different approaches. The first is based on a linear programming approach, the second is by use of distance-based algorithm (which uses a measure of the distance between a point and a convex cone); the third approach makes use of a matrix multiplication, which results in much faster dominance checks with respect to the preference relation induced by the trade-offs. Furthermore, we show that our trade-offs approach, which is based on a preference inference technique, can also be given an alternative semantics based on the well known Multi-Attribute Utility Theory. Our comprehensive experimental results on common multi-objective constraint optimization benchmarks demonstrate that the proposed enhancements allow the algorithms to scale up to much larger problems than before. For decision making problems under uncertainty, we describe multi-objective influence diagrams, based on a set of p objectives, where utility values are vectors in Rp, and are typically only partially ordered. These can be solved by a variable elimination algorithm, leading to a set of maximal values of expected utility. If the Pareto ordering is used this set can often be prohibitively large. We consider approximate representations of the Pareto set based on -coverings, allowing much larger problems to be solved. In addition, we define a method for incorporating user trade-offs, which also greatly improves the efficiency.

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Patients with life-threatening conditions sometimes appear to make risky treatment decisions as their condition declines, contradicting the risk-averse behavior predicted by expected utility theory. Prospect theory accommodates such decisions by describing how individuals evaluate outcomes relative to a reference point and how they exhibit risk-seeking behavior over losses relative to that point. The authors show that a patient's reference point for his or her health is a key factor in determining which treatment option the patient selects, and they examine under what circumstances the more risky option is selected. The authors argue that patients' reference points may take time to adjust following a change in diagnosis, with implications for predicting under what circumstances a patient may select experimental or conventional therapies or select no treatment.

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Contestants are predicted to adjust the cost of a fight in line with the perceived value of the resource and this provides a way of determining whether the resource has been assessed. An assessment of resource value is predicted to alter an animal's motivational state and we note different methods of measuring that state. We provide a categorical framework in which the degree of resource assessment may be evaluated and also note limitations of various approaches. We place studies in six categories: (1) cases of no assessment, (2) cases of internal state such as hunger influencing apparent value, (3) cases of the contestants differing in assessment ability, (4) cases of mutual and equal assessment of value, (5) cases where opponents differ in resource value and (6) cases of particularly complex assessment abilities that involve a comparison of the value of two resources. We examine the extent to which these studies support game theory predictions and suggest future areas of research. (C) 2008 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

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With the increasing pressure on social and health care resources, professionals have to be more explicit in their decision making regarding the long-term care of older people. This grounded theory study used 19 focus groups and nine semi-structured interviews (99 staff in total) to explore professional perspectives on this decision making. Focus group participants and interviewees comprised care managers, social workers, consultant geriatricians, general medical practitioners, community nurses, home care managers, occupational therapists and hospital discharge support staff. The emerging themes spanned context, clients, families and services. Decisions were often prompted by a crisis, hindering professionals seeking to make a measured assessment. Fear of burglary and assault, and the willingness and availability of family to help were major factors in decisions about living at home. Service availability in terms of public funding for community care, the availability of home care workers and workload pressures on primary care services influenced decision 'thresholds' regarding admission to institutional care. Assessment tools designed to assist decision making about the long-term care of older people need to take into account the critical aspects of individual fears and motivation, family support and the availability of publicly funded services as well as functional and medical needs.

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<p>This article reports results of an experiment designed to analyze the link between risky decisions made by couples and risky decisions made separately by each spouse. We estimate both the spouses and the couples' degrees of risk aversion, we assess how the risk preferences of the two spouses aggregate when they make risky decisions, and we shed light on the dynamics of the decision process that takes place when couples make risky decisions. We find that, far from being fixed, the balance of power within the household is malleable. In most couples, men have, initially, more decision-making power than women but women who ultimately implement the joint decisions gain more and more power over the course of decision making.</p>

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Decision making is an important element throughout the life-cycle of large-scale projects. Decisions are critical as they have a direct impact upon the success/outcome of a project and are affected by many factors including the certainty and precision of information. In this paper we present an evidential reasoning framework which applies Dempster-Shafer Theory and its variant Dezert-Smarandache Theory to aid decision makers in making decisions where the knowledge available may be imprecise, conflicting and uncertain. This conceptual framework is novel as natural language based information extraction techniques are utilized in the extraction and estimation of beliefs from diverse textual information sources, rather than assuming these estimations as already given. Furthermore we describe an algorithm to define a set of maximal consistent subsets before fusion occurs in the reasoning framework. This is important as inconsistencies between subsets may produce results which are incorrect/adverse in the decision making process. The proposed framework can be applied to problems involving material selection and a Use Case based in the Engineering domain is presented to illustrate the approach. 2013 Elsevier B.V. All rights reserved.

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Background: While significant strides have been made in health research, the incorporation of research evidence into healthcare decision-making has been marginal. The purpose of this paper is to provide an overview of how the utility of health services research can be improved through the use of theory. Integrating theory into health services research can improve research methodology and encourage stronger collaboration with decision-makers. Discussion: Recognizing the importance of theory calls for new expectations in the practice of health services research. These include: the formation of interdisciplinary research teams; broadening the training for those who will practice health services research; and supportive organizational conditions that promote collaboration between researchers and decision makers. Further, funding bodies can provide a significant role in guiding and supporting the use of theory in the practice of health services research. Summary: Institutions and researchers should incorporate the use of theory if health services research is to fulfill its potential for improving the delivery of health care. 2005 Brazil et al; licensee BioMed Central Ltd.

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Critical decisions are made by decision-makers throughout<br/>the life-cycle of large-scale projects. These decisions are crucial as they<br/>have a direct impact upon the outcome and the success of projects. To aid<br/>decision-makers in the decision making process we present an evidential<br/>reasoning framework. This approach utilizes the Dezert-Smarandache<br/>theory to fuse heterogeneous evidence sources that suffer from levels<br/>of uncertainty, imprecision and conflicts to provide beliefs for decision<br/>options. To analyze the impact of source reliability and priority upon<br/>the decision making process, a reliability discounting technique and a<br/>priority discounting technique, are applied. A maximal consistent subset<br/>is constructed to aid in dening where discounting should be applied.<br/>Application of the evidential reasoning framework is illustrated using a<br/>case study based in the Aerospace domain.

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The cognitive reflection test (CRT) is a short measure of a person's ability to resist intuitive response tendencies and to produce a normatively correct response, which is based on effortful reasoning. Although the CRT is a very popular measure, its psychometric properties have not been extensively investigated. A major limitation of the CRT is the difficulty of the items, which can lead to floor effects in populations other than highly educated adults. The present study aimed at investigating the psychometric properties of the CRT applying item response theory analyses (a two-parameter logistic model) and at developing a new version of the scale (the CRT-long), which is appropriate for participants with both lower and higher levels of cognitive reflection. The results demonstrated the good psychometric properties of the original, as well as the new scale. The validity of the new scale was also assessed by measuring correlations with various indicators of intelligence, numeracy, reasoning and decision-making skills, and thinking dispositions. Moreover, we present evidence for the suitability of the new scale to be used with developmental samples. Finally, by comparing the performance of adolescents and young adults on the CRT and CRT-long, we report the first investigation into the development of cognitive reflection.

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The nature and challenges of public sector leadership and management are examined in four case studies of project management in complex metropolitan environments. The cases selected by the authors as representative of contextual factors affecting decision-making processes and project outcomes. Drawing on recent theoretical work on complex leadership approaches (Uhl-Bein et al 2007, Hazy 2008, Lichtenstein &amp; Plowman 2009), the authors assess leadership practices enacted and the circumstances that influence these practices. Leadership types theorized by Uhl-Bein et al (2007) are identified operating at different levels and across networks, with contextual factors outlined. The article concludes with a framework for leadership practice and management identifying network facilitation and complexity friendly tools as a practice within complex public sector systems.

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This paper presents a Multi-Agent Market simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agents reactions.

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Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.