Maximization and Search for Alternatives in Decision Situations With and Without Loss of Options

Maximizing tendency has been associated with greater accumulation of choice alternatives prior to selection of a preference. It is not known whether this search behavior extends to situations in which accumulation of new choice alternatives comes with the potential loss of existing ones. In Study 1, we replicate the original finding of greater accumulation of choice alternatives, using a computer‐based laboratory task. We then provide evidence, in Studies 2 and 3, that when potential loss of existing options is incorporated into the task, maximization is associated with less rather than more search for additional options. Maximization components of decision difficulty and alternative search, but not high standards or satisficing, explain this behavior. Other task measures are also collected, but few maximization‐related differences are observed. The findings support an interpretation of maximizers as decision makers who are as concerned with the potential loss of existing options as with the loss of undiscovered future ones. Copyright © 2015 John Wiley & Sons, Ltd.     

The cognitive and neural basis of option generation and subsequent choice

Decision-making research has thoroughly investigated how people choose from a set of externally provided options. However, in ill-structured real-world environments, possible options for action are not defined by the situation but have to be generated by the agent. Here, we apply behavioral analysis (Study 1) and functional magnetic resonance imaging (Study 2) to investigate option generation and subsequent choice. For this purpose, we employ a new experimental task that requires participants to generate options for simple real-world scenarios and to subsequently decide among the generated options. Correlational analysis with a cognitive test battery suggests that retrieval of options from long-term memory is a relevant process during option generation. The results of the fMRI study demonstrate that option generation in simple real-world scenarios recruits the anterior prefrontal cortex. Furthermore, we show that choice behavior and its neural correlates differ between self-generated and externally provided options. Specifically, choice between self-generated options is associated with stronger recruitment of the dorsal anterior cingulate cortex. This impact of option generation on subsequent choice underlines the need for an expanded model of decision making to accommodate choice between self-generated options.     

Developmental patterns of change in the influence of safe and risky peer choices on risky decision‐making

Adolescents take more risks when peers monitor their behavior. However, it is largely unknown how different types of peer influence affect adolescent decision‐making. In this study, we investigate how information about previous choices of peers differentially influences decision‐making in adolescence and young adulthood. Participants (N = 99, age range 12–22) completed an economic choice task in which choice options were systematically varied on levels of risk and ambiguity. On each trial, participants selected between a safer choice (low variability in outcome) and a riskier choice (high variability in outcome). Participants made choices in three conditions: a solo condition in which they made choices with no additional information, a social condition in which they saw choices of supposed peers, and a computer condition in which they saw choices of a computer. Results showed that participants’ choices conform to the choices made by the peers, but not a computer. Furthermore, when peers chose the safe option, late adolescents were especially likely to make a safe choice. Conversely, when the peer made a risky choice, late adolescents were least likely to follow choices made by the peer. We did not find evidence for differential influence of social information on decisions depending on their level of risk and ambiguity. These results show that information about previous decisions of peers are a powerful modifier for behavior and that the effect of peers on adolescents’ decisions is less ubiquitous and more specific than previously assumed.     

Probability matching in risky choice: The interplay of feedback and strategy availability

Probability matching in sequential decision making is a striking violation of rational choice that has been observed in hundreds of experiments. Recent studies have demonstrated that matching persists even in described tasks in which all the information required for identifying a superior alternative strategy—maximizing—is present before the first choice is made. These studies have also indicated that maximizing increases when (1)?the asymmetry in the availability of matching and maximizing strategies is reduced and (2)?normatively irrelevant outcome feedback is provided. In the two experiments reported here, we examined the joint influences of these factors, revealing that strategy availability and outcome feedback operate on different time courses. Both behavioral and modeling results showed that while availability of the maximizing strategy increases the choice of maximizing early during the task, feedback appears to act more slowly to erode misconceptions about the task and to reinforce optimal responding. The results illuminate the interplay between “top-down” identification of choice strategies and “bottom-up” discovery of those strategies via feedback.     

When mixed options are preferred in multiple‐trial decisions

We report three studies showing that in prospective multiple‐trial decisions people often select a mix of sure and risky options over pure bundles of either option. Such a preference is not ‘rational’ because a mixed option cannot be the EV‐maximizing choice. Experiment 1 confirmed a mixed‐option preference for gains but not for losses. Showing a graph of the multiple‐trial outcome distribution reduced but did not eliminate this effect, suggesting that it is not due purely to a failure to aggregate correctly over the multiple trials. Experiment 2 replicated the mixed option preference using a wider range of problems. Experiment 3 compared choices in the trinary choice conditions used in Experiments 1 and 2 with binary choices between pairs of the multiple‐trial sure, mixed, and risky options. In the binary choice condition the mixed option was no longer the modal choice, suggesting that the strong mixed option preference found in the trinary choice conditions is mainly due to a compromise effect. However, the binary choice probabilities did show violations of strong stochastic transitivity in a pattern that suggested a slight bias toward the mixed option. Copyright © 2006 John Wiley & Sons, Ltd.     

自我框架、风险认知和风险选择

对行为决策中“框架效应”(Framing Effect)的研究进行了拓展：探讨了自我框架对风险决策的影响及其机制。面对运用图示方法表示的管理,健康,及投资方面的风险决策问题,参与者自主地选择对方案的描述（自我框架）。研究有四个主要发现：1）自我框架对风险选择的效应部分显著,而且对风险选择的影响方向因情境的不同而不同;2）机会威胁认知是自我框架效应的一个中介变量;3）自我框架在情绪语气上的差异对风险决策有显著影响：决策者对一个备选方案（确定性或风险性方案）相对于另一个备选方案的自我描述的情绪语气越积极正面,这个方案被选择的可能性越大;4）决策者的机会-威胁认知是这一自我框架效应的部分中介变量。也就是说,对备选方案的自我描述语气作为一种对决策信息的编码影响了风险（机会和威胁）认知,进而影响决策者的风险偏好和选择     

Choice-Process Satisfaction: The Influence of Attribute Alignability and Option Limitation

This research investigates how choice-process satisfaction is influenced by limitation of choice option and by the types of features used to represent the options. Studies of choice satisfaction have focused on how satisfied the decision maker feels about the choice that has been made and have overlooked the importance of the process through which the decision maker makes a choice, i.e., choice-process satisfaction. We show that the comparability of choice options through alignable features increases choice-process satisfaction, whereas option limitation (i.e., making one option unavailable from a set of equally attractive options) decreases choice-process satisfaction. Further, this decrease in satisfaction, relative to all options being available, occurs for people who are given a set of options in which the difference features are alignable (i.e., differences of a corresponding dimension) but not for people who are given a set of options in which the difference features are nonalignable (i.e., differences of unique dimensions). We propose that alignable differences are easier to compare and have more weight in people's attribute processing, and thus give rise to a perception of a greater amount of information about the option set that is relevant for choice. Making an option unavailable in this case would have a bigger impact than in a situation in which all options have nonalignable differences. Nonalignable differences are difficult to process and are less likely to make people aware that there is very much information about the options for decision making. This explanation and the interaction effect between option limitation and feature alignability are tested in four experiments.     

Preference for oddity: uniqueness heuristic or hierarchical choice process?

Traditional economic theories assume decision makers in multialternative choice tasks "assign" a value to each option and then express rational preferences. Here, I report an apparent violation of such rationality in gray jays (Perisoreus canadensis). I tested the jays' preference in a quaternary choice task where three options were the same color and the fourth option was a different color. All options offered an identical food reward and so the strictly rational expectation was that subjects would choose the odd-colored option in 25% of choices. In clear disagreement, every subject chose the odd option more frequently than expected. I speculate as to how this surprising preference for oddity might have been ecologically rational: by using a unique-choice heuristic, the jays might have been able to bypass a deliberative phase of the decision process and devote more attention to scanning for predators. Alternatively, it is conceivable that the jays did not prefer oddity per se. Instead, they might have used a hierarchical process, assigning options to color categories and then choosing between categories. If so, their behavior matches expectation after all (on average, subjects chose the odd option 50% of the time). It should be straightforward to test these competing hypotheses. The current results can be viewed as a new example of how simple mechanisms sometimes produce economically puzzling yet ecologically rational decision making.     

Risking Everything in Obsessive–Compulsive Disorder: An Analogue Decision-Making Study

An experiment examined decision-making processes among nonclinical participants with low or high levels of OCD symptomatology (N?=?303). To better simulate the decision environments that are most likely to be problematic for clients with OCD, we employed decision tasks that incorporated “black swan” options that have a very low probability but involve substantial loss. When faced with a choice between a safer option that involved no risk of loss or a riskier alternative with a very low probability of substantial loss, most participants chose the safer option regardless of OCD symptom level. However, when faced with choices between options that had similar expected values to the previous choices, but where each option had some low risk of a substantial loss, there was a significant shift towards riskier decisions. These effects were stronger when the task involved a contamination based, health-relevant decision task as compared to one with financial outcomes. The results suggest that both low and high symptom OC participants approach decisions involving risk-free options and decisions involving risky alternatives in qualitatively different ways. There was some evidence that measures of impulsivity were better predictors of the shift to risky decision making than OCD symptomatology.

     

Maximizing Scales Do Not Reliably Predict Maximizing Behavior in Decisions from Experience

In this paper, we explore the relationships between psychometric and behavioral measures of maximization in decisions from experience (DfE). In two experiments, we measured choice behavior in two experimental paradigms of DfE and self‐reported maximizing tendencies using three prominent scales of maximization. In the repeated consequentialist choice paradigm, participants made repeated choices between two unlabeled options and received consequential feedback on each trial. In the sampling paradigm, participants freely sampled from two options and received feedback on their sampling before making a single consequential choice. Individuals exhibited different degrees of maximizing behavior in both paradigms and across different payoff distributions, but none of the maximizing scales predicted this behavior. These results indicate that maximization scales address constructs that are different from the maximization behavior observed in DfE, and that these measures will need to be improved to reflect behavioral aspects of choice and search from experience. Copyright © 2017 John Wiley & Sons, Ltd.     

Banking on a bad bet. Probability matching in risky choice is linked to expectation generation

Probability matching is the tendency to match choice probabilities to outcome probabilities in a binary prediction task. This tendency is a long-standing puzzle in the study of decision making under risk and uncertainty, because always predicting the more probable outcome across a series of trials (maximizing) would yield greater predictive accuracy and payoffs. In three experiments, we tied the predominance of probability matching over maximizing to a generally adaptive cognitive operation that generates expectations regarding the aggregate outcomes of an upcoming sequence of events. Under conditions designed to diminish the generation or perceived applicability of such expectations, we found that the frequency of probability-matching behavior dropped substantially and maximizing became the norm.     

When, what, and how much to reward in reinforcement learning-based models of cognition

Reinforcement learning approaches to cognitive modeling represent task acquisition as learning to choose the sequence of steps that accomplishes the task while maximizing a reward. However, an apparently unrecognized problem for modelers is choosing when, what, and how much to reward; that is, when (the moment: end of trial, subtask, or some other interval of task performance), what (the objective function: e.g., performance time or performance accuracy), and how much (the magnitude: with binary, categorical, or continuous values). In this article, we explore the problem space of these three parameters in the context of a task whose completion entails some combination of 36 state-action pairs, where all intermediate states (i.e., after the initial state and prior to the end state) represent progressive but partial completion of the task. Different choices produce profoundly different learning paths and outcomes, with the strongest effect for moment. Unfortunately, there is little discussion in the literature of the effect of such choices. This absence is disappointing, as the choice of when, what, and how much needs to be made by a modeler for every learning model.     

Which is the compromise option? Information format and task format as determinants

When consumers must make a decision but are uncertain of their preferences, they often select a compromise choice. Early studies emphasized the relational properties of choice alternatives and indicated that the middle option, whose attribute values fall between the values of other alternatives, is always the compromise option. More recent studies have suggested that when consumers rate two attributes with the same metrics, the attribute–balance choice whose two attributes have equal ratings, might represent the compromise choice. We propose that the different characteristics of the middle and attribute–balance options—which may be compatible with certain determinants such as information and task formats—might be more salient and affect the relative attractiveness of each option. The results of three experiments confirmed this prediction: the middle option was more attractive in list‐by‐attributes and rejecting conditions, whereas the attribute–balance option was more attractive in list‐by‐alternatives and choosing conditions. Copyright © 2007 John Wiley & Sons, Ltd.     

Understanding variability in binary and continuous choice

Excessive variability in binary choice (categorical judgment) can take the form of probability matching rather than the normatively correct behavior of deterministically choosing the more likely alternative. Excessive variability in continuous choice (judgment rating) can take the form of underconfidence, understating the probability of highly likely events and overstating the probability of very unlikely events. We investigated the origins of choice variability in terms of noise prior to decision (at the evidence stage) and at the decision stage. A version of the well-known medical diagnosis task was conducted with binary and continuous choice on each trial. Noise at evidence stage was reduced by allowing the subjects to view historical summaries of prior relevant trials, and noise at the decision stage was reduced by giving the subjects a numerical score on the basis of their continuous choice and the actual outcome. Both treatments greatly reduced variability. Cash payments based on the numerical score had a less reliable incremental effect in our experiment. The overall results are more consistent with a Logit model of decision than with a simple criterion (or maximization) rule or a simple probabilitymatching rule.     

Computational models for the combination of advice and individual learning

Decision making often takes place in social environments where other actors influence individuals' decisions. The present article examines how advice affects individual learning. Five social learning models combining advice and individual learning-four based on reinforcement learning and one on Bayesian learning-and one individual learning model are tested against each other. In two experiments, some participants received good or bad advice prior to a repeated multioption choice task. Receivers of advice adhered to the advice, so that good advice improved performance. The social learning models described the observed learning processes better than the individual learning model. Of the models tested, the best social learning model assumes that outcomes from recommended options are more positively evaluated than outcomes from nonrecommended options. This model correctly predicted that receivers first adhere to advice, then explore other options, and finally return to the recommended option. The model also predicted accurately that good advice has a stronger impact on learning than bad advice. One-time advice can have a long-lasting influence on learning by changing the subjective evaluation of outcomes of recommended options.     

BROADENING THE DEFINITION OF DECISION MAKING:

Decision theory and research have focused almost exclusively on choice—the selection of the best option from a choice set containing two or more options. Largely overlooked is the question of how those particular options got there in the first place—why them and not others? This article describes a theory, called image theory, about how prechoice screening of options governs the contents of the set from which a choice is made and summarizes empirical tests of the theory. The research results suggest that screening plays afar more important role in decision making than is generally appreciated and that our view of decision making must be broadened accordingly.     

Beyond the gambling paradigm: internal controllability in decision-making.

Much research within decision-making has used the standard gambling paradigm, where decision outcomes depend only on chance. Many real life decisions, however, imply personal control over decision outcomes. This paper addressed the question of how internal controllability influences decision-making. Internal controllability is assumed (i) to enhance unrealistic optimism and (ii) to result in a better cost:benefit ratio. Both tendencies support each other and predict an enhanced attractiveness for internal and controllable choice options. Participants read a scenario and made a decision afterwards. Results supported the prediction: decision-makers take the option they can personally control. This finding widens the narrow perspective inherent in much previous research based on the gambling paradigm.     

Sampling and decision rules used by honey bees in a foraging arena

Animals must continuously choose among various available options to exploit the most profitable resource. They also need to keep themselves updated about the values of all available options, since their relative values can change quickly due to depletion or exploitation by competitors. While the sampling and decision rules by which foragers profitably exploit a flower patch have attracted a great deal of attention in theory and experiments with bumble bees, similar rules for honey bee foragers, which face similar foraging challenges, are not as well studied. By presenting foragers of the honey bee Apis cerana with choice tests in a foraging arena and recording their behavior, we investigate possible sampling and decision rules that the foragers use to choose one option over another and to track other options. We show that a large part of the sampling and decision-making process of a foraging honey bee can be explained by decomposing the choice behavior into dichotomous decision points and incorporating the cost of sampling. The results suggest that a honey bee forager, by using a few simple rules as part of a Bayesian inference process, is able to effectively deal with the complex task of successfully exploiting foraging patches that consist of dynamic and multiple options.     

The impact of phantom decoys on choices in cats

Context-dependent choice is an important aspect of decision making. The paper examines context-dependent choice in cats (Felis catus), with particular reference to the effect of local context, on the basis of hypotheses developed in the field of human decision making. Cats were initially confronted with two different feeding options. This binary choice set was later manipulated incorporating a decoy that was better than the available options but ultimately unavailable (a phantom). By means of a within-subjects manipulation of phantom location in the attribute space, the author compared the effects of close and distant phantoms on the final choices. The main finding is that close phantom decoys affected choice behavior of cats by altering the overall share of the available options, leading some animals to reject even some of the available feeding options, and by causing the animals to favor the available option that was more similar to the phantom decoy. No significant effects emerged for phantoms that were far from the alternatives in the attribute space. The strengths of this paper lie in its novel approach and high originality. No other study has used dominating decoys with animals or decoys that are unattainable. This paper provides strong links to the human decision making literature, the presentation of the predictions of a range of different choice models, and the novelty of the application to animals. The use of a phantom decoy is particularly interesting because the phantom cannot actually be chosen, and thus the binary and trinary choice sets both have the very same choices available. Overall, the effect of phantoms is real, interesting and new.