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Learning the probabilities of multiple events from the environment is an important core competency of any organism. In our within‐participant experiment, participants experienced samples from two distributions, or prospects, each comprised of two to four events, and were required to provide simultaneous, rather than sequential, judgment of the likelihood of the complete set of observed events. Empirical calibration curves that map experienced probabilities to subjective probabilities reveal that the degree of underextremity (overestimation of low likelihood events and underestimation of high likelihood events) is strongly conditional on the number of judged events. We uncover two regularities conditional on the number of events that modify (a) the crossover points of the calibration curves with the identity line and (b) the gradient or sensitivity of probability judgments. We present a process model of elicited (subjective) probabilities that captures these empirical regularities. Experienced events recalled from memory may be erroneously attributed to the wrong events based on the similarity of event outcomes. We conclude that the observed miscalibration of probability judgments can be attributed to the noisy retrieval component of a rational process‐based decision model. We discuss the implications of our model for the conflicting empirical findings of overweighting and underweighting in the decisions from experience literature. Finally, we show that reliance on small samples can be an ecologically rational strategy for a bounded rational decision‐maker (subject to noisy recall), as aggregated subjective probabilities are closer to the ecological probabilities than the experienced (or sampled) probabilities are. [ABSTRACT FROM AUTHOR]

We test empirically the strategic counterpart of the Adaptive Decision Maker hypothesis (Payne, Bettman, & Johnson, 1993), which states that decision makers adapt their attention and decision rules to time pressure in predictable ways. For 29 normal form games, we test whether players adapt to tightening time constraints by reducing their information search and shifting to less computationally demanding heuristics, ultimately leading to systematic changes in choices. We specify process models of each decision rule, thereby allowing us to rank the rules by complexity on the basis of the number of elementary information processing units required to execute each rule. The frequency of decision rule use conditional on time constraints is estimated using Bayesian latent class modeling. Under time pressure, the subject pool displayed a systematic shift toward heuristics of less complexity. We observed an increase in nonstrategic decision rules (particularly Level 1) and rules that choose the social optimum at the expense of more complex rules including the Nash equilibrium. Also, subjects are more likely to not acquire information about others' payoffs, thus effectively transforming the games into nonstrategic situations. The subjects' adaptation to time pressure was efficient in the sense that it did not lead to significant payoff losses.

Models of heuristics are often predicated on the desideratum that they should possess no free parameters. As a result, heuristic implementations are usually deterministic and do not allow for any choice errors, as the latter would require a parameter to regulate the magnitude of errors. We discuss the implications of this in light of research that highlights the evidence supporting stochastic choice and its dependence on preferential strength. We argue that, in principle, the existing models of deterministic heuristics should, and can, be quite easily modified to stochastic counterparts through the addition of an errormechanism. This requires a single free parameter in the error mechanism, whilst otherwise retaining the parameter-free cognitive processes in the deterministic component of existing heuristics. We present various types of error mechanisms applicable to heuristics and discuss their comparative virtues and drawbacks, paying particular attention to their impact on model comparisons between heuristics and parameter-rich models. [ABSTRACT FROM AUTHOR]

We determined the scope of five decision models of choices across four environmental niches defined by whether outcome probabilities are described (risk) or experienced by sampling (uncertainty) and whether lotteries are simple (one or two outcomes per prospect) or complex (three or four). The majority of participants chose in accordance with cumulative prospect theory only in simple environments involving decisions from description (75%). In complex environments involving decisions from description and experience, however, skewness-preference models were more prevalent (57% and 68%, respectively). Consequently, in niches outside of simple lotteries under risk, rank dependence and nonlinear probability weighting failed to accurately describe the majority of choices. Exploiting elicited subjective beliefs in decisions from experience, we found that experienced (sampled) outcome likelihoods outperformed elicited beliefs in predicting choices and found scant evidence for two-stage models of decisions under uncertainty. Finally, we found statistically significant evidence that 90% of participants chose as if they relied on different models across environments; nonetheless, assuming as if participants used a single model across all environments to predict out-of-sample choice only minimally reduced prediction accuracy. We discuss the implications of model mimicry and task diagnosticity in light of these results in terms of both economic and statistical significance, both for model comparisons and inference. [ABSTRACT FROM AUTHOR]

Ecological rationality represents an alternative to classic frameworks of rationality. Extending on Herbert Simon's concept of bounded rationality, it holds that cognitive processes, including simple heuristics, are not per se rational or irrational, but that their success rests on their degree of fit to relevant environmental structures. The key is therefore to understand how cognitive and environmental structures slot together. In recent years, a growing set of analyses of heuristic–environment systems has deepened the understanding of the human mind and how boundedly rational heuristics can result in successful decision making. This article is concerned with three conceptual challenges in the study of ecological rationality. First, do heuristics also succeed in dynamic contexts involving competitive agents? Second, can the mind adapt to environmental structures via an unsupervised learning process? Third, how can research go beyond mere descriptions of environmental structures to develop theories of the mechanisms that give rise to those structures? In addressing these questions, we illustrate that a successful theory of rationality will focus on the adaptive aspects of the mind and will need to account for three components: the mind's information processing, the environment to which the mind adapts, and the intersection between the environment and the mind. Ecological rationality represents an alternative to classic frameworks of rationality. Extending on Herbert Simon's concept of bounded rationality, it holds that cognitive processes, including simple heuristics, are not per se rational or irrational, but that their success rests on their degree of fit to relevant environmental structures. This article features new answers to three conceptual challenges in the study of this mind‐environment fit. [ABSTRACT FROM AUTHOR]

Adherence to social norms is compromised in a variety of neuropsychiatric conditions. Functional neuroimaging studies have investigated social norm compliance in healthy individuals, leading to the identification of a network of fronto-subcortical regions that underpins this ability. However, there is a lack of corroborative evidence from human lesion models investigating the structural anatomy of norm compliance across this fronto-subcortical network. To address this, we developed a neuroeconomic task to investigate social norm compliance in a neurodegenerative lesion model: behavioural variant frontotemporal dementia, a condition characterized by gross social dysfunction. The task assessed norm compliance across three behaviours that are well-studied in the neuroeconomics literature: fairness, prosocial and punishing behaviours. We administered our novel version of the Ultimatum Game in 22 patients with behavioural variant frontotemporal dementia and 22 age-matched controls, to assess how decision-making behaviour was modulated in response to (i) fairness of monetary offers; and (ii) social context of monetary offers designed to produce either prosocial or punishing behaviours. Voxel-based morphometry was used to characterize patterns of grey matter atrophy associated with task performance. Acceptance rates between patients and controls were equivalent when only fairness was manipulated. However, patients were impaired in modulating their decisions in response to social contextual information. Patients' performance in the punishment condition was consistent with a reduced tendency to engage in punishment; this was associated with decreased grey matter volume in the anterior cingulate, orbitofrontal cortex, left dorsolateral prefrontal cortex and right inferior frontal gyrus. In the prosocial condition, patients' performance suggested a reduced expression of prosocial behaviour, associated with decreased grey matter in the anterior insula, lateral orbitofrontal cortex, anterior cingulate and dorsal striatum. Acceptance rates in the Ultimatum Game were also significantly related to impairments in the everyday expression of empathic concern. In conclusion, we demonstrate that compliance to basic social norms (fairness) can be maintained in behavioural variant frontotemporal dementia; however, more complex normative behaviours (prosociality, punishment) that require integration of social contextual information are disrupted in association with atrophy in key fronto-striatal regions. These results suggest that the integration of social contextual information to guide normative behaviour is uniquely impaired in behavioural variant frontotemporal dementia, and may explain other common features of the condition including gullibility and impaired empathy. Our findings also converge with previous functional neuroimaging investigations in healthy individuals and provide the first description of the structural anatomy of social norm compliance in a neurodegenerative lesion model. [ABSTRACT FROM AUTHOR]