Ambiguous Decision Research Articles

Analysis of an Co-phasing detecting method based on far-field images of sparse-optical-synthetic-aperture system

For the sparse-optical-synthetic-aperture telescope system, the co-phasing detection plays an important role for the realization of system's high resolution in solving out piston errors between sub-apertures. In this paper, the relationship between piston error and system's far-field intensity was analyzed based on physical principles, then the impact of piston error on system's far-field images was clarified theoretically. Furthermore, an innovative co-phasing detecting method based on the far-field images' similarity was approved for the bi-sub-aperture systems, with its feasibility, detecting deviation and dynamic range were researched by simulation. The results proved that, with this method, the piston error between the system's two sub-apertures can be soundly detected principally while immune from the problems of 2 ambiguity and direction decision that might exist within some other co-phasing detecting methods. Plus its dynamic range shown from these results, this new co-phasing detecting method provides effective references for deeper research of co-phasing detecting techniques.

Eliciting Ambiguity Aversion in Unknown and in Compound Lotteries: A KMM Experimental Approach

We define coherent-ambiguity aversion within the Klibano¤, Marinacci and Mukerji (2005) smooth ambiguity model (henceforth KMM) as the combination of choice-ambiguity aversion and value-ambiguity aversion. We analyze theoretically ?ve ambiguous decision tasks, where a subject faces two-stage lotteries with binomial, uniform or unknown second-order probabilities. We check our theoretical predictions through a 10-task laboratory experiment. In (unambiguous) tasks 1-5, we elicit risk aversion both through a portfolio choice method and through a BDM mechanism. In (ambiguous) tasks 6-10, we elicit choice-ambiguity aversion through the portfolio choice method and value-ambiguity aversion through the BDM mechanism. We ?nd that more than 75% of classi?ed subjects behave according to the KMM model in all tasks 6-10, independent of their degree of risk aversion. Further, the percentage of coherently-ambiguity-averse subjects is lower in the binomial than in the uniform and in the unknown treatment, with only the latter di¤erence being signi?cant. Finally, highly-risk-averse subjects are more prone to coherent-ambiguity.

Prediction of surface roughness in magnetic abrasive finishing using acoustic emission and force sensor data fusion

The configuration of automated polishing systems requires the implementation of monitoring schemes to estimate surface roughness. In this study, a precision polishing process – magnetic abrasive finishing (MAF) – was investigated together with an in-process monitoring set-up. A specially designed magnetic quill was connected to a CNC machining center to polish the surface of Stavax (S136) die steel workpieces. During finishing experiments, both acoustic emission (AE) signals and force signals were sampled and analyzed. The finishing results show that MAF has nanoscale finishing capability (up to 8nm in surface roughness), and the sensor signals have strong correlations with parameters such as the gap between the tool and workpiece, feed rate, and abrasive size. In addition, the signals were utilized as input parameters of artificial neural networks (ANNs) to predict generated surface roughness. To increase accuracy and resolve ambiguities in decision making/prediction from the vast amount of data generated, sensor data fusion (AE + force)-based ANN and sensor information-based ANN were constructed. Among the three types of networks, the ANN constructed using sensor fusion produced the most stable outcomes. The results of this analysis demonstrate that the proposed sensor (fusion) scheme is appropriate for monitoring and prediction of nanoscale precision finishing processes.

Management Insights

Management Insights

Managerial Responsibility as Negotiated Order: A Social Construction Perspective

This article examines how employees form their perceptions of managerial responsibility in a concrete organizational setting. Drawing on negotiated order theory, it shows that these perceptions are the result of complex processes of social construction and negotiation, rather than the application of predetermined ethics models or norms. Employees’ perceptions appear to be unstable; they are subject to constant alterations, fluctuating with the organizational circumstances, and are likely to create considerable organizational perturbations, especially when managers make complex and ambiguous decisions. This process is illustrated through an ethnographic study that analyzed the evolution of employee perceptions during a three-year crisis—one that led managers to repeatedly postpone salary payments to save jobs. The process approach adopted by the study highlights important dynamics that traditional business ethics approaches overlook, such as the fragility of the construct of managerial responsibility, which cannot be coherent unless it is constantly renegotiated among an organization’s various employee groups.

Effects of meaning and sense of words on semantic ambiguity in lexical decision

Effects of meaning and sense of words on semantic ambiguity in lexical decision

Navigating Ambiguity: Comedy Improvisation as a Tool for Urban Design Pedagogy and Practice

The purpose of this article is three-fold: to reflect critically on the nature of comedy improvisation as a method of unleashing individual and collaborative creativity, to investigate its application in studio pedagogy as a way of enhancing the design process, and to offer insights into its effectiveness as a pedagogical tool and its implications for urban design practice. While comedy improvisation has been studied and applied in fields such as business and management, there has been no serious attempt to explore its potential as an urban design methodology. Based on the author’s experience as a professional urban designer and extensive training in comedy improvisation, an experimental urban design studio was conducted in Boston for graduate students at Massachusetts Institute of Technology in early 2009. The article highlights the benefits of comedy improvisation such as creative collaboration, fostering innovation, supporting spontaneity, and learning through error; and describes the studio experience of building skills and testing ideas through pedagogical practice. The article concludes with useful insights from comedy improvisation for urban design practice, including building effective design teams as horizontal networks, developing highly creative design processes that are sensitive to constant change, and ways in which design innovation emerges out of specific types of group dynamics. Urban designers require such skills in a field marked by long-term non-linear design processes, interdisciplinary teams and multiple stakeholders with different viewpoints, and considerable ambiguity in decision making.

Abstract 1917: Immunological Tumor Maps: a Landscape of Infiltrating Immune Cells in Colorectal Cancer Based on Complete Tissue Section Analyses

Abstract In colorectal cancer (CRC) large scale tissue microarray (TMA) based quantitative immune cell counts using immune cell surface molecules (CD3, CD8, Granzyme B, and CD45RO) have identified the number of infiltrating immune cells to be potentially better predictors for patient survival than the classical TNM system. The spatial heterogeneity of immune cells may not be well reflected in the highly selected, and typically small (0,6-1 mm2) tissue cores of the TMA. This represents an obstacle in the individual prognosis prediction or classification of a single patient. To investigate this aspect, the localization and distribution of immune cell subpopulations based on the analysis of complete tissue sections by a dedicated novel staining and imaging system were performed. Using a specialized staining platform and whole slide imaging & analysis by virtual microscopy (VM), immunological “tumor maps” were generated. These tumor maps are based on cell densities in fields of 1mm2 size, visualizing intratumoral heterogeneity for the surface markers CD3, CD8, Granzyme B, and CD45RO. In total, an area of 867 mm2 was automatically evaluated with an average of 48 mm2 of evaluated tumor tissue per patient slide. Cell counts varied within a patient significantly, ranging from 0 to up to 2550 cells / mm2. Further analyses revealed, that sampling of single field counts within the tumor can only yield clear diagnostic decisions for a fraction of the analyzed patients, with ambiguous decisions for 11 out of 20 patients. Interestingly, the overall degree of heterogeneity also varied between patients, with lower heterogeneity found only in samples with lower cell counts. No samples with a homogeneous high cell density distribution were observed. The observed variability has implications for the individual prognosis prediction and represents the first spatial quantitative study of immune cells in a set of CRC primary tumors. The presented tumor maps therefore are a suitable tool to visualize heterogeneity. Furthermore, whole slide imaging & analysis by VM is essential in the identification of prognostic markers as well as in their subsequent application. In the future, spatial marker signatures could contribute to individual patient classification. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1917.

Alterations of decision making and underlying neural correlates after resection of a mediofrontal cortical dysplasia: A single case study

We investigated the impact of a congenital prefrontal lesion and its resection on decision making under risk and under ambiguity in a patient with right mediofrontal cortical dysplasia. Both kinds of decision making are normally associated with the medial prefrontal cortex. We additionally studied pre- and postsurgical fMRI activations when processing information relevant for risky decision making. Results indicate selective impairments of ambiguous decision making pre- and postsurgically. Decision making under risk was intact. In contrast to healthy subjects the patient exhibited no activation within the dysplastic anterior cingulate cortex but left-sided orbitofrontal activation on the fMRI task suggesting early reorganization processes.

Beneath the Surface: Intranational Institutions and Management of the United States — Mexico Transboundary Santa Cruz Aquifer

As reliance on groundwater increases, the impact of groundwater-intensive use in internationally shared aquifers threatens not only to create negative environmental and economic externalities, but also to generate tensions between neighboring nations. Through an investigation of the shared Santa Cruz aquifer, located along the United States—Mexico border, we aim to understand factors leading to effective management of transboundary groundwaters. Specifically, we find that purely state-centric approaches provide limited explanatory value, and instead examine how national (domestic) arrangements for water management condition a country's position vis-à-vis its shared groundwaters. Polycentricism in national and subnational institutional regimes leads to gaps and overlaps in authority, limiting binational groundwater management. Concurrently, evolving institutional arrangements lead to ambiguity in decision making, yet crucially also provide opportunities for innovation in binational agenda setting and data sharing, which in turn aid in the alignment of both countries' priorities for the transboundary Santa Cruz aquifer.

A fuzzy logic-based approach to idea screening for product design

The idea screening of a new product concept is perhaps the most critical activity in new product development (NPD). This paper presents a fuzzy synthetic evaluation method (FSEM) for selecting an optimum design alternatives based on fuzzy set theory. The process involves constructing a hierarchical objective, setting evaluation criteria, establishing a fuzzy judgment matrix and weight vector, and then ranking the order of design alternatives by a fuzzy number in the fuzzy sequencing vector. A hierarchical structure is used to calculate the fuzzy probability level by level from the lowest-level objectives. The evaluation objectives are arranged in the hierarchical structure with several levels. The relative contribution of each objective to the overall value of the solution and the rating or degree of approximation of a solution with respect to a given objective are quantified with the membership functions of a fuzzy set. After the fuzzy expected values of the top-level objectives are calculated, they are then used to make a decision quantitatively on selecting the optimal design alternative. The proposed approach can efficiently aid managers in dealing with both ambiguity and complexity in product screening decisions. To verify the feasibility of this approach, a case study is conducted with a product design of Power Line Communication (PLC) in this study.

A Paradox for the ''Smooth Ambiguity'' Model of Preference

Two Ellsberg-style thought experiments are described that reflect on the smooth ambiguity decision model developed by Klibanoff, Marinacci, and Mukerji (2005). The first experiment poses difficulties for the model's axiomatic foundations and, as a result, also for its interpretation, particularly for the claim that the model achieves a separation between ambiguity and the attitude toward ambiguity. Given the problematic nature of its foundations, the behavioral content of the model and how it differs from multiple priors, for example, are not clear. The second thought experiment casts some light on these questions.

Ambiguous decision trees for mining concept-drifting data streams

In real world situations, explanations for the same observations may be different depending on perceptions or contexts. They may change with time especially when concept drift occurs. This phenomenon incurs ambiguities. It is useful if an algorithm can learn to reflect ambiguities and select the best decision according to context or situation. Based on this viewpoint, we study the problem of deriving ambiguous decision trees from data streams to cope with concept drift. CVFDT (Concept-adapting Very Fast Decision Tree) is one of the most well-known streaming data mining methods that can learn decision trees incrementally. In this paper, we establish a method called ambiguous CVFDT (aCVFDT), which integrates ambiguities into CVFDT by exploring multiple options at each node whenever a node is to be split. When aCVFDT is used to make class predictions, it is guaranteed that the best and newest knowledge is used. When old concepts recur, aCVFDT can immediately relearn them by using the corresponding options recorded at each node. Furthermore, CVFDT does not automatically detect occurrences of concept drift and only scans trees periodically, whereas an automatic concept drift detecting mechanism is used in aCVFDT. In our experiments, hyperplane problem and two benchmark problems from the UCI KDD Archive, namely Network Intrusion and Forest CoverType, are used to validate the performance of aCVFDT. The experimental results show that aCVFDT obtains significantly improved results over traditional CVFDT.

The role of affect and tolerance of ambiguity in ethical decision making

Abstract This research note extends the research on ethical decision making in accounting by examining the effect of two variables, affect and tolerance of ambiguity, on ethics-related decisions made in two contexts: both personal and organizational settings. I conduct an experimental study among undergraduate accounting students and find that tolerance of ambiguity significantly influences ethical decisions in both personal and organizational settings. The results also reveal a significant interactive effect between negative affect and tolerance of ambiguity.

Recursive smooth ambiguity preferences

This paper axiomatizes an intertemporal version of the Smooth Ambiguity decision model developed in [P. Klibanoff, M. Marinacci, S. Mukerji, A smooth model of decision making under ambiguity, Econometrica 73 (6) (2005) 1849–1892]. A key feature of the model is that it achieves a separation between ambiguity, identified as a characteristic of the decision maker's subjective beliefs, and ambiguity attitude, a characteristic of the decision maker's tastes. In applications one may thus specify/vary these two characteristics independent of each other, thereby facilitating richer comparative statics and modeling flexibility than possible under other models which accommodate ambiguity sensitive preferences. Another key feature is that the preferences are dynamically consistent and have a recursive representation. Therefore techniques of dynamic programming can be applied when using this model.

Decentralized diagnosis based on Boolean discrete event models: application on manufacturing systems

This paper proposes a decentralized structure based on a set of local diagnosers to monitor discrete event manufacturing systems with discrete sensors and actuators. The occurrence of any fault entailing the violation of the desired behaviour must be detected and isolated by at least one local diagnoser using its own local observation about the system execution. These local diagnosers infer the fault's occurrence using event sequences, time delays between correlated events and state conditions, characterized by sensors readings and commands issued by the controller. A very limited communication among diagnosers is permitted through a simple coordinator based on a set of rules. The goal is to solve the problem of diagnosis's decision ambiguity due to the partial observation of diagnosers. An adapted codiagnosability notion is formally defined in order to ensure that the set of local diagnosers is able to diagnose all faults entailing the violation of the desired behaviour within a bounded delay. We show that the construction of these diagnosers is polynomial in the size of the system. An example is used to illustrate the proposed approach.

New approach to multiple attribute decision making with interval numbers

In an ambiguous decision domain, the evaluation values of alternatives against attributes would be interval numbers because of the inherent, uncertain property of the problems. By using a number of linear programming models, Bryson and Mobolurin propose an approach to compute attribute weights and overall values of the alternatives in the form of interval numbers. The intervals of the overall values of alternatives are then transformed into points or crisp values for comparisons among the alternatives. However, the attribute weights are different because of the use of linear programming models in Bryson and Mobolurin's approach. Thus, the alternatives are not comparable because different attribute weights are employed to calculate the overall values of the alternatives. A new approach is proposed to overcome the drawbacks of Bryson and Mobolurin's approach. By transforming the decision matrix with intervals into the one with crisp values, a new linear programming model is proposed, to calculate the attribute weights for conducting alternative ranking.

Impact of ambiguity and risk on decision making in mild Alzheimer's disease

Decisions under ambiguity and decisions under risk are crucial types of decision making in daily living at any age. This is the first study assessing these two types of decisions in patients with mild dementia of Alzheimer's type (DAT) by means of the Iowa Gambling Task (IGT) and a newly developed, Probability-Associated Gambling (PAG) task. While rules for gains and losses are implicit in the IGT, in the PAG task rules are explicit and winning probabilities, which change from trial to trial, can be estimated. Results of the IGT indicated that DAT patients made more disadvantageous decisions than healthy controls. Patients also shifted more frequently among decks, i.e. under ambiguity decisions were taken randomly and no advantageous strategy was established over time by DAT patients. Thus, not only actual choices but also development of advantageous strategies may be revealing about decision making in the IGT. Compared to controls, patients demonstrated less advantageous choices in the PAG task as well. They gambled more often in the low winning probabilities and less frequently in the high probabilities than healthy participants. Patients’ performance on both tasks correlated with measures of executive functions. Findings of the present investigation are consistent with the early pathological cerebral changes and related (cognitive, emotional) deficits reported for DAT. As suggested by our study, decisions under ambiguity as well as decisions under risk are impaired in mild DAT. It may thus be expected that patients with mild DAT have difficulties in taking decisions in every-day life situations, both in cases of ambiguity (information on probability is missing or conflicting, and the expected utility of the different options is incalculable) and in cases of risk (outcomes can be predicted by well-defined or estimable probabilities).

Political Stability Under Uncertainty: Applying Bounded Rationality to the Study of Governance and Civil Conflict

Acentral puzzle in the comparative politics literature has been why certain societies are able to achieve political stability while others suffer from strife, repression and authoritarian rule. This article applies the solution concept of quantal response equilibrium (QRE) to Weingast's Sovereign-Constituency Co-ordination Game in order to show how our understanding of political stability can be enhanced when uncertainty and limited rationality are explicitly modelled. Comparative statics results first confirm the intuitive logic that civil conflict is unlikely when regimes threaten penalties for revolt that are much more severe than current living conditions and when the benefits to a successful revolt are not sufficiently enticing. In addition, our analysis provides a logic for the outbreak of civil conflict, noting that it is most likely when key payoffs are in their intermediate regions and far from critical ‘thresholds’, resulting in ambiguous and counterintuitive decision making by leaders and citizen opposition groups.

Activation of Prefrontal Cortex by Transcranial Direct Current Stimulation Reduces Appetite for Risk during Ambiguous Decision Making

As adult humans, we are continuously faced with decisions in which proper weighing of the risk involved is critical. Excessively risky or overly cautious decision making can both have disastrous real-world consequences. Weighing of risks and benefits toward decision making involves a complex neural network that includes the dorsolateral prefrontal cortex (DLPFC), but its role remains unclear. Repetitive transcranial magnetic stimulation studies have shown that disruption of the DLPFC increases risk-taking behavior. Transcranial direct current stimulation (tDCS) allows upregulation of activity in the DLPFC, and we predicted that it might promote more cautious decision making. Healthy participants received one of the following treatments while they performed the Balloon Analog Risk Task: (1) right anodal/left cathodal DLPFC tDCS, (2) left anodal/right cathodal DLPFC tDCS, or (3) sham tDCS. This experiment revealed that participants receiving either one of the bilateral DLPFC tDCS strategies adopted a risk-averse response style. In a control experiment, we tested whether unilateral DLPFC stimulation (anodal tDCS over the right or left DLPFC with the cathodal electrode over the contralateral supraorbital area) was sufficient to decrease risk-taking behaviors. This experiment showed no difference in decision-making behaviors between the groups of unilateral DLPFC stimulation and sham stimulation. These findings extend the notion that DLPFC activity is critical for adaptive decision making, possibly by suppressing riskier responses. Anodal tDCS over DLPFC by itself did not significantly change risk-taking behaviors; however, when the contralateral DLPFC was modulated with cathodal tCDS, an important decrease in risk taking was observed. Also, the induced cautious decision-making behavior was observed only when activity of both DLPFCs was modulated. The ability to modify risk-taking behavior may be translated into therapeutic interventions for disorders such as drug abuse, overeating, or pathological gambling.