Sensitivity analysis with interdependent criteria for multicriteria decision making: The case of soil pollution treatment

This paper is focused on interdependences between criteria in multicriteria decision analyses. Such interdependences are usually ignored in sensitivity analyses. After a discussion on the nature of interdependences, methods are presented to deal with interdependences in the context of Monte Carlo experiments. These methods are applied in the context of soil pollution treatment alternatives. It is shown that ignoring interdependences may have a distorting effect on the results of sensitivity analysis on rankings of alternatives.     

An evolutionary approach to support decision making with linear decision models

In this paper we consider decision problems that can be described as linear decision models. These models have been traditionally solved using linear programming, fuzzy linear programming, multiple-objective linear programming or ‘what-if’ analysis. Using these approaches, one encounters a number of difficulties. We propose an ‘evolutionary approach’ to overcome these difficulties. In the proposed approach the decision maker does not have to precisely specify the model (i.e. the objective functions, the RHS values, etc.) at the beginning of the solution procedure. In fact, the model evolves as the solution procedure proceeds.     

An application of a dual-process approach to decision making in social dilemmas

This study compared psychological and behavioral responses in a take-some social dilemma with those in a give-some situation and suggested an explanation in terms of a dual process model. Participants facing the take-some dilemma exhibited a higher level of cooperation than those facing the give-some dilemma only in their first decision trial, and this effect was independent of our experimental manipulation of the information processing mode. Furthermore, once an experiential mode was induced, participants spent less time and experienced less conflict when making decisions in the take-some dilemma than in the give-some situations. The findings indicate that in social dilemmas the information processing mode has a stronger effect on psychological responses than on behavioral responses.     

The choice of constraints in correspondence analysis

A discussion of alternative constraint systems has been lacking in the literature on correspondence analysis and related techniques. This paper reiterates earlier results that an explicit choice of constraints has to be made which can have important effects on the resulting scores. The paper also presents new results on dealing with missing data and probabilistic category assignment.I am most grateful to the following for their helpful comments. Arto Demirjian, Michael Greenacre, Michael Healy, Shizuhiko Nishisato, Roderick Mcdonald, and several anonymous referees.     

On the application of J.M. Keynes's approach to decision making

It is shown that J. M. Keynes was the originator of what is called a weighted monetary value (WMV) approach to decision making under uncertainty and risk as opposed to either the expected monetary value (EMV) or subjective expected utility (SEU) approaches.     

The impact of task complexity on information use in multi-attribute decision making

This study presents a process analysis of multi-attribute decision making. The decision problems concerned the selection of the most suitable candidate for a job opening. The problems varied in terms of complexity, i.e. the number of candidates and the number of attributes used to describe these alternatives. Results show that with an increasing number of alternatives, subjects (N = 48) used fewer attributes for the evaluation of alternatives, and made, on average, less references to the alternatives. The type of judgment most often used was absolute dimensional (comparison of an attribute to an absolute standard) and was used more often at the beginning than toward the end of the decision process. Overall, judgments were predominantly positive. The percentage of positive judgments decreased with increasing complexity, and toward the end of the decision process. Significantly more judgments, particularly positive ones, concerned the finally chosen alternative as compared to the rest of the alternatives. Finally, analysis of subjects' usage of decision rules revealed that increasing the number of alternatives resulted in an increasing use of elimination strategies. Implications of these findings for the design of decision aids will be discussed.     

A neural cognitive model of argumentation with application to legal inference and decision making

Formal models of argumentation have been investigated in several areas, from multi-agent systems and artificial intelligence (AI) to decision making, philosophy and law. In artificial intelligence, logic-based models have been the standard for the representation of argumentative reasoning. More recently, the standard logic-based models have been shown equivalent to standard connectionist models. This has created a new line of research where (i) neural networks can be used as a parallel computational model for argumentation and (ii) neural networks can be used to combine argumentation, quantitative reasoning and statistical learning. At the same time, non-standard logic models of argumentation started to emerge. In this paper, we propose a connectionist cognitive model of argumentation that accounts for both standard and non-standard forms of argumentation. The model is shown to be an adequate framework for dealing with standard and non-standard argumentation, including joint-attacks, argument support, ordered attacks, disjunctive attacks, meta-level attacks, self-defeating attacks, argument accrual and uncertainty. We show that the neural cognitive approach offers an adequate way of modelling all of these different aspects of argumentation. We have applied the framework to the modelling of a public prosecution charging decision as part of a real legal decision making case study containing many of the above aspects of argumentation. The results show that the model can be a useful tool in the analysis of legal decision making, including the analysis of what-if questions and the analysis of alternative conclusions. The approach opens up two new perspectives in the short-term: the use of neural networks for computing prevailing arguments efficiently through the propagation in parallel of neuronal activations, and the use of the same networks to evolve the structure of the argumentation network through learning (e.g. to learn the strength of arguments from data).     

A noniterative method of joint correspondence analysis

Correspondence analysis leads to a graphical representation of the associations between categories of the row and column variables of a contingency table. Greenacre's (1988) formulation of joint correspondence analysis is a multivariate extension which finds the optimal joint display of contingency tables between all pairs of variables in a set. Greenacre presented a discrepancy function and an alternating least squares algorithm for its minimization. Boik (1996) presented an alternative algorithm, also of the alternating least squares type, for minimizing the same discrepancy function. In this paper, a noniterative procedure, not based on the minimization of any discrepancy function, is described.     

Targets and tactics: The analysis of moment-to-moment decision making in animal combat

Even though injury and death are more common consequences of fighting among animals than once believed, they are still relatively infrequent. Modern evolutionary models of animal combat have emphasized that given the threat of retaliation, animals only escalate to more injurious fighting if the benefits outweigh the costs, and then only if threat and bluff fail to achieve the goal. Such models stress the role of communication as to whether animals decide to escalate or not. An alternative view is that failure to produce injury or death arises from the neutralization of one animal's attack by another's defense. That is, attack and defense end in a stalemate that may be misinterpreted by outside observers as an absence of injury producing behavior. As attack typically involves the biting or striking of specific body targets, movements and postures occurring during combat need to be analyzed with respect to their role in gaining or averting such contact. For example, in the combat of muroid rodents the attacker targets the lower dorsum and flanks (low threshold) or face (high threshold), whereas a defender may defensively launch counterstrikes against the attacker's face. Two combat tactics (supine defense and lateral attack) typically present in the fighting of muroid rodents are analyzed in detail to illustrate how targets constrain the movements of combatants. Such a functional analysis of combat assumes that the movements and postures performed are related to their role in the attack and defense of targets. Deviations from such a strict functional interpretation reveal some of the other factors that may constrain the combatants' behavior. For example, body morphology and the aggressiveness of the opponent are shown to be important in deciding the type of combat tactic to use and how it is performed. Finally, movements and postures that are neutral or even counterproductive for attack and defense may be revealed as communicatory. This approach provides a means of analyzing behavior during the "heat of combat" that is typically not dealt with in traditional evolutionary models. Aggr. Behav. 23:107–129, 1997.© 1997 Wiley-Liss, Inc.     

The principle of additivity and its relation to clinical decision making

Clients (N = 178) with varying degrees of organic indicators were administered a psychological battery including the Memory for Designs Test (MFD; Graham & Kendall, 1960) to assess the extent to which joint presence of organic indicators affected the sensitivity of the MFD in identifying organicity. Joint presence failed to add to the discriminability of the MFD, although individual instruments such as the PIAT (Arithmetic) and WAIS-R (PIQ less than VIQ) clearly discriminated across the MFD.     

Compressing movement information via principal components analysis (PCA): Contrasting outcomes from the time and frequency domains

PCA has become an increasingly used analysis technique in the movement domain to reveal patterns in data of various kinds (e.g., kinematics, kinetics, EEG, EMG) and to compress the dimension of the multivariate data set recorded. It appears that virtually all movement related PCA analyses have, however, been conducted in the time domain (PCA_t). This standard approach can be biased when there are lead-lag (phase-related) properties to the multivariate time series data. Here we show through theoretical derivation and analysis of simulated and experimental postural kinematics data sets that PCA_t and, PCA in the frequency domain (PCA_f), can lead to contrasting determinations of the dimension of a data set, with the tendency of PCA_t to overestimate the number of components. PCA_f also provides the possibility of obtaining amplitude and phase-difference spectra for each principal component that are uniquely suitable to reveal control mechanisms of the system. The bias in the PCA_t estimate of the number of components can have significant implications for the veracity of the interpretations drawn in regard to the dynamical degrees of freedom of the perceptual-motor system.     

Quantitative analysis of finger motion coordination in hand manipulative and gestic acts

This article reports an experimental study that aimed to quantitatively analyze motion coordination patterns across digits 2-5 (index to little finger), and examine the kinematic synergies during manipulative and gestic acts. Twenty-eight subjects (14 males and 14 females) performed two types of tasks, both right-handed: (1) cylinder-grasping that involved concurrent voluntary flexion of digits 2-5, and (2) voluntary flexion of individual fingers from digit 2 to 5 (i.e., one at a time). A five-camera opto-electronic motion capture system measured trajectories of 21 miniature reflective markers strategically placed on the dorsal surface landmarks of the hand. Joint angular profiles for 12 involved flexion-extension degrees of freedom (DOF's) were derived from the measured coordinates of surface markers. Principal components analysis (PCA) was used to examine the temporal covariation between joint angles. A mathematical modeling procedure, based on hyperbolic tangent functions, characterized the sigmoidal shaped angular profiles with four kinematically meaningful parameters. The PCA results showed that for all the movement trials (n = 280), two principal components accounted for at least 98% of the variance. The angular profiles (n = 2464) were accurately characterized, with the mean (+/-SD) coefficient of determination (R2) and root-mean-square-error (RMSE) being 0.95 (+/-0.12) and 1.03 degrees (+/-0.82 degrees ), respectively. The resulting parameters which quantified both the spatial and temporal aspects of angular profiles revealed stereotypical patterns including a predominant (87% of all trials) proximal-to-distal flexion sequence and characteristic interdependence--involuntary joint flexion induced by the voluntarily flexed joint. The principal components' weights and the kinematic parameters also exhibited qualitatively similar variation patterns. Motor control interpretations and new insights regarding the underlying synergistic mechanisms, particularly in relation to previous findings on force synergies, are discussed.     

The enduring impact of transient emotions on decision making

People often do not realize they are being influenced by an incidental emotional state. As a result, decisions based on a fleeting incidental emotion can become the basis for future decisions and hence outlive the original cause for the behavior (i.e., the emotion itself). Using a sequence of ultimatum and dictator games, we provide empirical evidence for the enduring impact of transient emotions on economic decision making. Behavioral consistency and false consensus are presented as potential underlying processes.     

The role of chance events in career decision making

Two studies are reported that investigate the role of chance events as influences in career decision making. In study one, the results of a large-scale survey of high-school and university students (N = 772) investigating influences on their career decision making are presented. Chance events were reported as influencing the career decisions of 69.1% of the sample. In the second study, the role of locus of control was found to be moderately associated with reporting chance events. More External control individuals tend to report more chance events than their Internal control counterparts. Implications for career choice theory and research are discussed.     

The role of ambiguity tolerance in career decision making

The role of ambiguity tolerance in career decision making was examined in a sample of college students (n = 275). Three hypotheses were proposed regarding the direct prediction of ambiguity tolerance on career indecision, the indirect prediction of ambiguity tolerance on career indecision through environmental and self explorations, and the moderation effect of ambiguity tolerance on the link of environmental and self explorations with career indecision. Results supported the significance of ambiguity tolerance with respect to career indecision, finding that it directly predicted general indecisiveness, dysfunctional beliefs, lack of information, and inconsistent information, and moderated the prediction of environmental exploration on inconsistent information. The implications of this study are discussed and suggestions for future research are provided.     

The effect of visual signals on spatial decision making

We examined the effect of an irrelevant visual transient on the decision where to look for a hidden object. Participants also performed a conventional ‘inhibition of return’ localization task. In Experiments 1 and 2 the two tasks were blocked and in Experiments 3 and 4 they were randomly interleaved. In every experiment there was a bias to select the cued location in the spatial decision task. This facilitory effect was greatest when the cue occurred at a strategically unfavored location and even occurred for participants who reported strategically selecting a non-cued location, indicating that the facilitory effect is automatic and independent of other strategic biases. Inhibition of return was observed only when the tasks were blocked and the localization task preceded the decision task. The findings suggests that spatial decisions engage different attentional control settings than those engaged when detecting visual transients; and that this attentional mode affects the processing of visual transients such that they do not inhibit the subsequent speeded detection of onset targets.     

The effect of age on decision making according to the Iowa gambling task

Aging has been associated with several brain changes that often affect the cognitive functioning of adults, but changes in executive functions, particularly in the field of decision making, have not been fully investigated. The Iowa Gambling Task (IGT) is a widely used tool to evaluate decision making, but little is known about the effect of age on its results. This study used the IGT and compared healthy young (n = 40) and elderly (n = 40) adults to evaluate their decision making processes. There were significant differences in the learning curve of the two age groups, but no difference in overall IGT performance. The results for the first IGT block were different from those of the rest of the task, and the group of elderly adults had a better performance in this block. Elderly adults also showed a preference for deck A, the one that resulted in greater losses. Findings confirmed the results of other studies, which reported that the IGT block score is the variable with the greatest sensitivity to age in this instrument.     

Processes of patient decision making: Theoretical and methodological issues

Abstract

There is a paucity of research studying patients' decision making processes. Traditional normative approaches investigating human decision have presented rational, analytic processing as a ‘gold standard’ for decision making with decision aids developed to facilitate such thinking. This paradigm has been challenged by the recent emergence of naturalistic decision making. Naturalistic approaches argue for techniques modelled closer to how decisions are actually made in ‘real life’. Early work in this evolving field suggests the importance of more automatic, intuitive processing such as the use of heuristic short-cuts. This paper discusses the contribution of naturalistic decision theory and assesses its usefulness as an alternative to classical decision approaches in investigating patient decision making. Approaches for measuring underlying cognitive processes are also critically discussed.     

A dual-process approach to health risk decision making: The prototype willingness model

Although dual-process models in cognitive, personality, and social psychology have stimulated a large body of research about analytic and heuristic modes of decision making, these models have seldom been applied to the study of adolescent risk behaviors. In addition, the developmental course of these two kinds of information processing, and their relation to the development of self-regulation are not well understood at this time. The current paper reviews what leading dual-process models have to say about the development of analytic and heuristic decision making, and their implications for adolescent risk behavior. In addition, it reviews research on the prototype willingness model of adolescent decision making—a dual-process model designed specifically to address non-intentional, but volitional adolescent risk behavior. It also discusses the implications of dual-process models for intervention research.     

The operation of Lake Kariba: A multiobjective decision analysis

The paper describes a successful application of Bayesian decision analysis to the operation of the Lake Kariba hydropower system. This management problem is complicated by the high uncertainty of the inflow process, multiple and conflicting objectives and the influence of time on some of the parameters in the management task. Inflows to the reservoir are forecast through dynamic linear models. Managerial preferences are modelled through a multiattribute utility function. Since the solution of the exact model is computationally too demanding, a heuristic method is applied to find a feasible control strategy. A comparison with results obtained by methods used previously demonstrates the superiority of the methodology presented here.