Individual differences in causal learning and decision making

In judgment and decision making tasks, people tend to neglect the overall frequency of base-rates when they estimate the probability of an event; this is known as the base-rate fallacy. In causal learning, despite people's accuracy at judging causal strength according to one or other normative model (i.e., Power PC, DeltaP), they tend to misperceive base-rate information (e.g., the cause density effect). The present study investigates the relationship between causal learning and decision making by asking whether people weight base-rate information in the same way when estimating causal strength and when making judgments or inferences about the likelihood of an event. The results suggest that people differ according to the weight they place on base-rate information, but the way individuals do this is consistent across causal and decision making tasks. We interpret the results as reflecting a tendency to differentially weight base-rate information which generalizes to a variety of tasks. Additionally, this study provides evidence that causal learning and decision making share some component processes.     

Developmental and sex-related differences in preschoolers' affective decision making

This study investigated developmental and sex-related differences in affective decision making, using a two-deck version of Children's Gambling Task administered to 3- and 4-year-old children. The main findings were that 4-year-old children displayed better decision-making performance than 3-year-olds. This effect was independent of developmental changes in inductive reasoning, language, and working memory. There were also sex differences in decision-making performance, which were apparent only in 3-year-old children and favored girls. Moreover, age predicted awareness of task and the correlation between the latter and decision-making performance was significant, but only in 4-year-old children. This study thus indicates that there is a remarkable developmental leap in affective decision making, whose effects are apparent around the age of 4, which according to our results, also marks the age when the correlation of declarative knowledge and decision-making performance becomes significant.     

Individual differences in fast-and-frugal decision making: Neuroticism and the recognition heuristic

The fast-and-frugal recognition heuristic (RH) claims that people base inferences on recognition only, thus ignoring further knowledge they possess. This claim has been repeatedly challenged, while recent evidence suggests that there are substantial individual differences in adhering to the RH. However, no personality or ability factors driving (non-)use of the RH have, as yet, been identified. In the present study, neuroticism was hypothesized to be a determinant of using the RH: participants high in neuroticism were expected to avoid making use of their knowledge beyond recognition, thus avoiding a diagnostic test of their abilities. The results corroborate this hypothesis: neuroticism predicted participants’ adherence to the RH while the other Big 5 factors and intelligence yielded no additional explanatory power. Moreover, the effect of neuroticism was not mediated by the accessibility of knowledge thus lending preliminary support for the notion that this effect may, in fact, be genuinely motivational in nature.     

Myopic regret avoidance: Feedback avoidance and learning in repeated decision making

Decision makers can become trapped by myopic regret avoidance in which rejecting feedback to avoid short-term outcome regret (regret associated with counterfactual outcome comparisons) leads to reduced learning and greater long-term regret over continuing poor decisions. In a series of laboratory experiments involving repeated choices among uncertain monetary prospects, participants primed with outcome regret tended to decline feedback, learned the task slowly or not at all, and performed poorly. This pattern was reversed when decision makers were primed with self-blame regret (regret over an unjustified decision). Further, in a final experiment in which task learning was unnecessary, feedback was more often rejected in the self-blame regret condition than in the outcome regret condition. We discuss the findings in terms of a distinction between two regret components, one associated with outcome evaluation, the other with the justifiability of the decision process used in making the choice.     

Anatomy of a decision: striato-orbitofrontal interactions in reinforcement learning, decision making, and reversal

The authors explore the division of labor between the basal ganglia-dopamine (BG-DA) system and the orbitofrontal cortex (OFC) in decision making. They show that a primitive neural network model of the BG-DA system slowly learns to make decisions on the basis of the relative probability of rewards but is not as sensitive to (a) recency or (b) the value of specific rewards. An augmented model that explores BG-OFC interactions is more successful at estimating the true expected value of decisions and is faster at switching behavior when reinforcement contingencies change. In the augmented model, OFC areas exert top-down control on the BG and premotor areas by representing reinforcement magnitudes in working memory. The model successfully captures patterns of behavior resulting from OFC damage in decision making, reversal learning, and devaluation paradigms and makes additional predictions for the underlying source of these deficits.     

Implicit motor learning and complex decision making in time-constrained environments

The cost-effectiveness of the implicit (procedural) knowledge that supports motor expertise enables surprisingly efficient performance when a decision and an action must occur in close temporal proximity. The authors argue that if novices learn the motor component of performance implicitly rather than explicitly, then they will also be efficient when they make a decision and execute an action in close temporal proximity. Participants (N = 35) learned a table tennis shot implicitly or explicitly. The authors assessed participants' motor performance and movement kinematics under conditions that required a concurrent low-complexity decision or a concurrent high-complexity decision about where to direct each shot. Performance was disrupted only for participants who learned explicitly when they made high-complexity decisions but not when they made low-complexity decisions. The authors conclude that implicit motor learning encourages cognitively efficient motor control more than does explicit motor learning, which allows performance to remain stable when time constraints call for a complex decision in tandem with a motor action.     

Age differences in choice satisfaction: a positivity effect in decision making

The authors tested the possibility that older adults show a positivity effect in decision making, by giving younger and older adults the opportunity to choose 1 of 4 products and by examining the participants' satisfaction with their choice. The authors considered whether requiring participants to explicitly evaluate the options before making a choice has an effect on age differences in choice satisfaction. Older adults in the evaluation condition listed more positive and fewer negative attributes than did younger adults and were more satisfied with their decisions than were younger adults. There were no age differences among those who did not evaluate options. This evaluation-dependent elevation of satisfaction among older adults was still present when participants were contacted 2 weeks after the experiment. Age did not influence the accuracy with which participants predicted how their satisfaction would change over time.     

Latency differences in monoptic and dichoptic shape and color decision making

Past research based on the McCollough effect and efficacy of chromatic cues in stereopsis suggests that color information is difficult to process binocularly as compared to form information. This study evaluates this proposition using a reaction time paradigm. Subjects decided whether two simultaneous visual stimuli were the same in shape or color. With presentation to the same eye, color reaction times led shape latencies. Presenting one target to one eye and one to the other slowed color times. Delaying one target by 500 msec yielded dichoptic and monoptic color decisions faster than shape. The results are related to the relationships of color and contrast pathways and possible differences in binocular rivalry.     

Negative affectivity predicts individual differences in decision making for preschoolers

The authors' goal in conducting this study was to explore the association between temperament and future-oriented decision making. Forty-three preschoolers (mean age = 51 months) were given a child variant of the Iowa Gambling Task (IGT) and asked to choose between a deck with higher immediate rewards and a deck with higher future rewards. Children who were higher on the Extraversion/Surgency factor of the Child Behavior Questionnaire chose more frequently from the higher immediate rewards deck early in the game. The externalizing dimension of Negative Affectivity (anger/frustration, soothability and discomfort) made the greatest contribution to prediction of performance in the last block of the game. Children who were more easily frustrated and had difficulty regulating negative emotions chose more from the deck with higher immediate rewards. There was a significant interaction between the externalizing dimension of Negative Affectivity, the internalizing dimension of Negative Affectivity (sadness and fear) and Extraversion/Surgency on the last block. These results suggest a complex association between IGT performance and temperament in preschoolers.     

The importance of decision making in causal learning from interventions

Recent research has focused on how interventions benefit causal learning. This research suggests that the main benefit of interventions is in the temporal and conditional probability information that interventions provide a learner. But when one generates interventions, one must also decide what interventions to generate. In three experiments, we investigated the importance of these decision demands to causal learning. Experiment 1 demonstrated that learners were better at learning causal models when they observed intervention data that they had generated, as opposed to observing data generated by another learner. Experiment 2 demonstrated the same effect between self-generated interventions and interventions learners were forced to make. Experiment 3 demonstrated that when learners observed a sequence of interventions such that the decision-making process that generated those interventions was more readily available, learning was less impaired. These data suggest that decision making may be an important part of causal learning from interventions.     

Integrating advice and experience: learning and decision making with social and nonsocial cues

When making decisions, people typically gather information from both social and nonsocial sources, such as advice from others and direct experience. This research adapted a cognitive learning paradigm to examine the process by which people learn what sources of information are credible. When participants relied on advice alone to make decisions, their learning of source reliability proceeded in a manner analogous to traditional cue learning processes and replicated the established learning phenomena. However, when advice and nonsocial cues were encountered together as an established phenomenon, blocking (ignoring redundant information) did not occur. Our results suggest that extant cognitive learning models can accommodate either advice or nonsocial cues in isolation. However, the combination of advice and nonsocial cues (a context more typically encountered in daily life) leads to different patterns of learning, in which mutually supportive information from different types of sources is not regarded as redundant and may be particularly compelling. For these situations, cognitive learning models still constitute a promising explanatory tool but one that must be expanded. As such, these findings have important implications for social psychological theory and for cognitive models of learning.     

Type of learning task impacts performance and strategy selection in decision making

In order to be adaptive, cognition requires knowledge about the statistical structure of the environment. We show that decision performance and the selection between cue-based and exemplar-based inference mechanisms can depend critically on how this knowledge is acquired. Two types of learning tasks are distinguished: learning by comparison, by which the decision maker learns which of two objects has a higher criterion value, and direct criterion learning, by which the decision maker learns an object's criterion value directly. In three experiments, participants were trained either with learning by comparison or with direct criterion learning and subsequently tested with paired-comparison, classification, and estimation tasks. Experiments 1 and 2 showed that although providing less information, learning by comparison led to better generalization (at test), both when generalizing to new objects and when the task format at test differed from the task format during training. Moreover, learning by comparison enabled participants to provide rather accurate continuous estimates. Computational modeling suggests that the advantage of learning by comparison is due to differences in strategy selection: whereas direct criterion learning fosters the reliance on exemplar processing, learning by comparison fosters cue-based mechanisms. The pattern in decision performance reversed when the task environment was changed from a linear (Experiments 1 and 2) to a nonlinear structure (Experiment 3), where direct criterion learning led to better decisions. Our results demonstrate the critical impact of learning conditions for the subsequent selection of decision strategies and highlight the key role of comparison processes in cognition.     

Sex differences moderate decision making behaviour in high impulsive sensation seekers

We tested whether individuals with high levels of impulsive sensation seeking learn to choose advantageously in a specific decision-making context. One hundred twenty-eight participants (73 female) completed a neuropsychological task, the variant version of the Iowa Gambling Task (vIGT; Bechara, Tranel, & Damasio, 2000), in which individuals must select cards from decks that offer high initial losses if they are to eventually make a profit. The selection from decks of cards that led to the highest profit as the task progressed was higher in high, compared to low, impulsive sensation seekers. However, learning to choose advantageously was moderated by sex of participant. Specifically, compared to females, male high impulsive sensation seekers learned more quickly to make consistent selections from the advantageous decks despite the large immediate losses. Overall, the data support the hypothesis that insensitivity to loss due to impulsive sensation seeking can lead to financial gain.     

Intuitive decision making in complex situations: Somatic markers in an artificial grammar learning task

In this article, we explore the extent to which implicit learning is subtended by somatic markers, as evidenced by skin conductance measures. On each trial, subjects were asked to decide which “word” from a pair of “words” was the “correct” one. Unknown to the subjects, each “word” of a pair was constructed using a different set of rules (Grammar Aand Grammar B). A (monetary) reward was given if the subject chose the “word” from Grammar A. Choosing the Grammar B word resulted in (monetary) punishment. Skin conductance was measured during each of 100 trials. After each set of 10 trials, the subjects were asked how they selected the “correct word.” Task performance increased long before the subjects could even formulate a single relevant rule. In this preconceptual phase of the experiment, skin conductance was larger before incorrect than before correct choices. Thus, it was shown that artificial grammar learning is accompanied by a somatic marker, possibly “warning” the subject of the incorrect decision.     

Individual differences in need for cognition and decision making in the Iowa Gambling Task

Differences in decision making between individuals differing in Need for Cognition (NFC) are examined using the Iowa Gambling Task (IGT). Previous work using normative one time decisions suggests that individual low in NFC process gains and losses differently than those high in NFC and are more susceptible to decision biases. The IGT is a popular laboratory task that involves making risky decisions from experience involving both gains and losses. In the first experiment, low NFC participants performed significantly worse than the high NFC participants. A second experiment designed to examine the nature of these differences provides evidence that low NFC participants place more importance on gains as opposed to losses when performing the IGT. Results are discussed in light of previous work suggesting that low NFC participants place more importance on losses in mixed outcome decisions.     

Comparison of basic assumptions embedded in learning models for experience-based decision making

The present study examined basic assumptions embedded in learning models for predicting behavior in decisions based on experience. In such decisions, the probabilities and payoffs are initially unknown and are learned from repeated choice with payoff feedback. We examined combinations of two rules for updating past experience with new payoff feedback and of two choice rule assumptions for mapping experience onto choices. The combination of these assumptions produced four classes of models that were systematically compared. Two methods were employed to evaluate the success of learning models for approximating players’ choices: One was based on estimating parameters from each person’s data to maximize the prediction of choices one step ahead, conditioned by the observed past history of feedback. The second was based on making a priori predictions for the entire sequence of choices using parameters estimated from a separate experiment. The results indicated the advantage of a class of models incorporating decay of previous experience, whereas the ranking of choice rules depended on the evaluation method used.     

Fast and frugal heuristics and naturalistic decision making: a review of their commonalities and differences

Both the fast and frugal heuristics (FFHs) and the naturalistic decision making (NDM) research programmes have identified important areas of inquiry previously neglected in the traditional study of human judgment and decision making, and have greatly contributed to the understanding of people's real-world decision making under environmental constraints. The two programmes share similar theoretical arguments regarding the rationality, optimality, and role of experience in decision making. Their commonalities have made them appealing to each other, and efforts have been made, by their leading academics, to promote synergy and integration. However, there has been little progress towards this during the last decade. This paper seeks to address this gap by seeking to better understand their commonalities and differences. To do so, literature relating to the two programmes is reviewed. The findings of the review indicated that an integration of the two could enhance FFHs' field research in applied settings, facilitate its investigation on boundary conditions of people's decision strategy selection, enable NDM to embrace emerging research opportunities in the age of big data, as well as permit each programme to enlighten the research topics and to validate the research findings of the other.     

Knowledge management in decision making and decision support

A knowledge-oriented view of decisions and decision making is introduced, as a complement to classical perspectives and as a contribution of under-standing computer-based possibilities for relaxing strains on decision makers. This perspective includes a model of knowledge management activities performed by a decision maker and a taxonomy of knowledge types. It leads to a characterization of decision-support-system purpose, traits, and potentials that offers a basis for new research into computer-based possibilities for knowledge management. Clyde W. Holsapple holds the Rosenthal Endowed Chair in Management Information Systems and is Professor of Decision Science and Information Systems at the College of Business and Economics, University of Kentucky.     

Numeracy and decision making

A series of four studies explored how the ability to comprehend and transform probability numbers relates to performance on judgment and decision tasks. On the surface, the tasks in the four studies appear to be widely different; at a conceptual level, however, they all involve processing numbers and the potential to show an influence of affect. Findings were consistent with highly numerate individuals being more likely to retrieve and use appropriate numerical principles, thus making themselves less susceptible to framing effects, compared with less numerate individuals. In addition, the highly numerate tended to draw different (generally stronger or more precise) affective meaning from numbers and numerical comparisons, and their affective responses were more precise. Although generally helpful, this tendency may sometimes lead to worse decisions. The less numerate were influenced more by competing, irrelevant affective considerations. Analyses showed that the effect of numeracy was not due to general intelligence. Numerical ability appears to matter to judgments and decisions in important ways.