MEM-EX: An exemplar memory model of decisions from experience.

Many real-world decisions must be made on basis of experienced outcomes. However, there is little consensus about the mechanisms by which people make these decisions from experience (DfE). Across five experiments, we identified several factors influencing DfE. We also introduce a novel computational modeling framework, the memory for exemplars model (MEM-EX), which posits that decision makers rely on memory for previously experienced outcomes to make choices. Using MEM-EX, we demonstrate how cognitive mechanisms provide intuitive and parsimonious explanations for the effects of value-ignorance, salience, outcome order, and sample size. We also conduct a cross-validation analysis of several models within the MEM-EX framework. We compare these to three alternative models; two baseline models built on the principle of expected value maximization, and another employing a suite of choice methods previously shown to perform well in prediction tournaments. We find that MEM-EX consistently outperforms these competitors, demonstrating its value as a tool for making quantitative predictions without overfitting. We discuss the implications of these findings for our understanding of the interplay between attention, memory, and experience-based choice.

Formalizing the fundamental Faustian bargain: Inefficacious decision-makers sacrifice their freedom of choice to coercive leaders for economic security.

Individuals typically prefer the freedom to make their own decisions. Yet, people often trade their own decision control (procedural utility) to gain economic security (outcome utility). Decision science has not reconciled these observations. We examined how decision-makers' efficacy and security perceptions influence when, why, and how individuals exchange procedural and outcome utility. Undergraduate adults (N = 77; Mage = 19.45 years; 73% female; 62% Caucasian, 13% African American) were recruited from the psychology participant pool at a midwestern U.S. metropolitan university. Participants made financial decisions in easy and hard versions of a paid card task resembling a standard gambling task, with a learning component. During half the trials, they made decisions with a No-Choice Manager who controlled their decisions, versus a Choice Manager who granted decision control. The hard task was designed to be too difficult for most participants, undermining their efficacy and security, and ensuring financial losses. The No-Choice Manager was designed to perform moderately well, ensuring financial gains. Participants felt greater outcome satisfaction (utility) for financial gains earned via Choice, but not losses. Participants (85%) preferred the Choice manager in the easy task but preferred the No-Choice Manager (56%) in the hard task. This change in preference for choice corresponded with self-efficacy and was mediated by perceived security. We used Decision Field Theory to develop potential cognitive models of these decisions. Preferences were best described by a model that assumed decision-makers initially prefer Choice, but update their preference based on loss-dependent attentional focus. When they earned losses (hard task), decision-makers focused more on economic payoffs (financial security), causing them to deemphasize procedural utility. Losses competed for attention, pulling attention toward economic survivability and away from the inherent value of choice. Decision-makers are more likely to sacrifice freedom of choice to leaders they perceive as efficacious to alleviate perceived threats to economic security.

How top-down and bottom-up attention modulate risky choice.

We examine how bottom-up (or stimulus-driven) and top-down (or goal-driven) processes govern the distribution of attention in risky choice. In three experiments, participants chose between a certain payoff and the chance of receiving a payoff drawn randomly from an array of eight numbers. We tested the hypothesis that initial attention is driven by perceptual properties of the stimulus (e.g., font size of the numbers), but subsequent choice is goal-driven (e.g., win the best outcome). Two experiments in which task framing (goal driven) and font size (stimulus driven) were manipulated demonstrated that payoffs with the highest values and the largest font sizes had the greatest impact on choice. The third experiment added a number in large font to the array, which could not be an outcome of the gamble (i.e., a distractor). Eye movement and choice data indicated that although the distractor attracted attention, it had no influence on option selection. Together with computational modeling analyses, the results suggest that perceptual salience can induce bottom-up effects of overt selection but that the perceived value of information is the crucial arbiter of intentional control over risky choice.

Skilled bandits: Learning to choose in a reactive world.

In uncertain environments we must balance our need to gather information with our desire to reap rewards by exploiting current knowledge. Achieving this balance is further complicated in reactive environments where actions produce long-lasting change to the system. In four experiments, we investigate how people learn to make effective decisions from experience in a dynamic multiarmed bandit task. In contrast to the typical exploitation-dependent diminishing rewards found in previous studies, options were framed as skills that developed greater rewards the more they were chosen. In Experiment 1, we provide a proof of concept, and in Experiments 2-4 we explore the boundaries of participants' sensitivity to reactive dynamics. Our results suggest that most individuals can learn effective strategies for coping with these reactive environments. A two-part comparison of several competing psychological models supports several conclusions: (a) a sizable minority of individuals learned that their environment was reactive, (b) evidence suggests several distinct groups of individuals employed unique decision strategies, and (c) testing models with the simulation method reveals qualitative misfits that motivate future theory development. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Elucidating the differential impact of extreme-outcomes in perceptual and preferential choice.

When making decisions in complex environments we must selectively sample and process information with respect to task demands. Previous studies have shown that this requirement can manifest in the influence that extreme outcomes (i.e. values at the edges of a distribution) have on judgment and choice. We elucidate this influence via a task in which participants are presented, briefly, with an array of numbers and have to make one of two judgments. In 'preferential' judgments where the participants' goal was to choose between a safe, known outcome, and an unknown outcome drawn from the array, extreme-outcomes had a greater influence on choice than mid-range outcomes, especially under shorter time-limits. In 'perceptual' judgments where the participants' goal was to estimate the arrays' average, the influence of the extremes was less pronounced. A novel cognitive process model captures these patterns via a two-step selective-sampling and integration mechanism. Together our results shed light on how task goals modulate sampling from complex environments, show how sampling determines choice, and highlight the conflicting conclusions that arise from applying statistical and cognitive models to data.

How to Change the Weight of Rare Events in Decisions From Experience.

When people make risky choices, two kinds of information are crucial: outcome values and outcome probabilities. Here, we demonstrate that the juncture at which value and probability information is provided has a fundamental effect on choice. Across four experiments involving 489 participants, we compared two decision-making scenarios: one in which value information was revealed during sampling (standard) and one in which value information was revealed after sampling (value ignorance). On average, participants made riskier choices when value information was provided after sampling. Moreover, parameter estimates from a hierarchical Bayesian implementation of cumulative-prospect theory suggested that participants overweighted rare events when value information was absent during sampling but did not overweight such events in the standard condition. This suggests that the impact of rare events on choice relies crucially on the timing of probability and value integration. We provide paths toward mechanistic explanations of our results based on frameworks that assume different underlying cognitive architectures.

When the Good Looks Bad: An Experimental Exploration of the Repulsion Effect.

When people are choosing among different options, context seems to play a vital role. For instance, adding a third option can increase the probability of choosing a similar dominating option. This attraction effect is one of the most widely studied phenomena in decision-making research. Its prevalence, however, has been challenged recently by the tainting hypothesis, according to which the inferior option contaminates the attribute space in which it is located, leading to a repulsion effect. In an attempt to test the tainting hypothesis and explore the conditions under which dominated options make dominating options look bad, we conducted four preregistered perceptual decision-making studies with a total of 301 participants. We identified two factors influencing individuals' behavior: stimulus display and stimulus design. Our results contribute to a growing body of literature showing how presentation format influences behavior in preferential and perceptual decision-making tasks.

The Attraction Effect Modulates Reward Prediction Errors and Intertemporal Choices.

Classical economic theory contends that the utility of a choice option should be independent of other options. This view is challenged by the attraction effect, in which the relative preference between two options is altered by the addition of a third, asymmetrically dominated option. Here, we leveraged the attraction effect in the context of intertemporal choices to test whether both decisions and reward prediction errors (RPE) in the absence of choice violate the independence of irrelevant alternatives principle. We first demonstrate that intertemporal decision making is prone to the attraction effect in humans. In an independent group of participants, we then investigated how this affects the neural and behavioral valuation of outcomes using a novel intertemporal lottery task and fMRI. Participants' behavioral responses (i.e., satisfaction ratings) were modulated systematically by the attraction effect and this modulation was correlated across participants with the respective change of the RPE signal in the nucleus accumbens. Furthermore, we show that, because exponential and hyperbolic discounting models are unable to account for the attraction effect, recently proposed sequential sampling models might be more appropriate to describe intertemporal choices. Our findings demonstrate for the first time that the attraction effect modulates subjective valuation even in the absence of choice. The findings also challenge the prospect of using neuroscientific methods to measure utility in a context-free manner and have important implications for theories of reinforcement learning and delay discounting. SIGNIFICANCE STATEMENT: Many theories of value-based decision making assume that people first assess the attractiveness of each option independently of each other and then pick the option with the highest subjective value. The attraction effect, however, shows that adding a new option to a choice set can change the relative value of the existing options, which is a violation of the independence principle. Using an intertemporal choice framework, we tested whether such violations also occur when the brain encodes the difference between expected and received rewards (i.e., the reward prediction error). Our results suggest that neither intertemporal choice nor valuation without choice adhere to the independence principle.

The Dilution Effect and Information Integration in Perceptual Decision Making.

In cognitive science there is a seeming paradox: On the one hand, studies of human judgment and decision making have repeatedly shown that people systematically violate optimal behavior when integrating information from multiple sources. On the other hand, optimal models, often Bayesian, have been successful at accounting for information integration in fields such as categorization, memory, and perception. This apparent conflict could be due, in part, to different materials and designs that lead to differences in the nature of processing. Stimuli that require controlled integration of information, such as the quantitative or linguistic information (commonly found in judgment studies), may lead to suboptimal performance. In contrast, perceptual stimuli may lend themselves to automatic processing, resulting in integration that is closer to optimal. We tested this hypothesis with an experiment in which participants categorized faces based on resemblance to a family patriarch. The amount of evidence contained in the top and bottom halves of each test face was independently manipulated. These data allow us to investigate a canonical example of sub-optimal information integration from the judgment and decision making literature, the dilution effect. Splitting the top and bottom halves of a face, a manipulation meant to encourage controlled integration of information, produced farther from optimal behavior and larger dilution effects. The Multi-component Information Accumulation model, a hybrid optimal/averaging model of information integration, successfully accounts for key accuracy, response time, and dilution effects.

Theoretical developments in decision field theory: comment on Tsetsos, Usher, and Chater (2010).

Tsetsos, Usher, and Chater (2010) presented several criticisms of decision field theory (DFT) involving its distance function, instability under externally controlled stopping times, and lack of robustness to various multialternative choice scenarios. Here, we counter those claims with a specification of a distance function based on the indifference and dominance dimensions. Using this distance function, we show that the instability problems do not arise when using the internally controlled stopping rule. In conclusion, we argue that the predictions of DFT do not conflict with the data presented and that the model yet provides a coherent and accurate account of multialternative choice phenomena.

A causal model theory of the meaning of cause, enable, and prevent.

The verbs cause, enable, and prevent express beliefs about the way the world works. We offer a theory of their meaning in terms of the structure of those beliefs expressed using qualitative properties of causal models, a graphical framework for representing causal structure. We propose that these verbs refer to a causal model relevant to a discourse and that "A causes B" expresses the belief that the causal model includes a link from A to B. "A enables/allows B" entails that the model includes a link from A to B, that A represents a category of events necessary for B, and that an alternative cause of B exists. "A prevents B" entails that the model includes a link from A to B and that A reduces the likelihood of B. This theory is able to account for the results of four experiments as well as a variety of existing data on human reasoning.