Fermian guesstimation can boost the wisdom-of-the-inner-crowd.

How can people's ability to make accurate estimations be boosted? Psychological research on the wisdom-of-the-inner-crowd suggests that people's judgments improve when they use a simple consider-the-opposite-strategy, dubbed-inspired by Enlightenment philosopher Hegel-dialectical-bootstrapping: A person generates a first estimate (thesis), then rejects it and generates another one (anti-thesis), and finally integrates both (synthesis). Yet, the wisdom-of-the-inner-crowd-phenomenon comes with controversy concerning its measurement, robustness, and moderators. We (1) introduce a novel class of strategies to elicit the wisdom-of-the-inner-crowd.

Narratives, environments, and decision-making: A fascinating narrative, but one to be completed.

I encourage Johnson et al. to ground Conviction Narrative Theory in more detail in foundational, earlier decision-making research - first and foremost in Herbert Simon's work. Moreover, I wonder if and how further reflections about narratives could aid tackling two interrelated grand challenges of the decision sciences: To describe decision-making environments; to understand how people select among decision-strategies in environments.

How to model the neurocognitive dynamics of decision making: A methodological primer with ACT-R.

Higher cognitive functions are the product of a dynamic interplay of perceptual, mnemonic, and other cognitive processes. Modeling the interplay of these processes and generating predictions about both behavioral and neural data can be achieved with cognitive architectures. However, such architectures are still used relatively rarely, likely because working with them comes with high entry-level barriers.

Human-like machines: Transparency and comprehensibility.

Artificial intelligence algorithms seek inspiration from human cognitive systems in areas where humans outperform machines. But on what level should algorithms try to approximate human cognition? We argue that human-like machines should be designed to make decisions in transparent and comprehensible ways, which can be achieved by accurately mirroring human cognitive processes.

Reflections of the social environment in chimpanzee memory: applying rational analysis beyond humans.

In cognitive science, the rational analysis framework allows modelling of how physical and social environments impose information-processing demands onto cognitive systems. In humans, for example, past social contact among individuals predicts their future contact with linear and power functions. These features of the human environment constrain the optimal way to remember information and probably shape how memory records are retained and retrieved.

On theory integration: Toward developing affective components within cognitive architectures.

In The Cognitive-Emotional Brain, Pessoa (2013) suggests that cognition and emotion should not be considered separately. We agree with this and argue that cognitive architectures can provide steady ground for this kind of theory integration and for investigating interactions among underlying cognitive processes. We briefly explore how affective components can be implemented and how neuroimaging measures can help validate models and influence theory development.

Transferring control demands across incidental learning tasks - stronger sequence usage in serial reaction task after shortcut option in letter string checking.

After incidentally learning about a hidden regularity, participants can either continue to solve the task as instructed or, alternatively, apply a shortcut. Past research suggests that the amount of conflict implied by adopting a shortcut seems to bias the decision for vs. against continuing instruction-coherent task processing.

Once and for all--how people change strategy to ignore irrelevant information in visual tasks.

Ignoring irrelevant visual information aids efficient interaction with task environments. We studied how people, after practice, start to ignore the irrelevant aspects of stimuli. For this we focused on how information reduction transfers to rarely practised and novel stimuli.

Strategy selection: An introduction to the modeling challenge.

Modeling the mechanisms that determine how humans and other agents choose among different behavioral and cognitive processes-be they strategies, routines, actions, or operators-represents a paramount theoretical stumbling block across disciplines, ranging from the cognitive and decision sciences to economics, biology, and machine learning. By using the cognitive and decision sciences as a case study, we provide an introduction to what is also known as the strategy selection problem. First, we explain why many researchers assume humans and other animals to come equipped with a repertoire of behavioral and cognitive processes.

Processes models, environmental analyses, and cognitive architectures: quo vadis quantum probability theory?

A lot of research in cognition and decision making suffers from a lack of formalism. The quantum probability program could help to improve this situation, but we wonder whether it would provide even more added value if its presumed focus on outcome models were complemented by process models that are, ideally, informed by ecological analyses and integrated into cognitive architectures.

Decision making in a human population living sustainably.

The Tiwi people of northern Australia have managed natural resources continuously for 6000-8000 years. Tiwi management objectives and outcomes may reflect how they gather information about the environment. We qualitatively analyzed Tiwi documents and management techniques to examine the relation between the social and physical environment of decision makers and their decision-making strategies.

Heuristic decision making in medicine.

Can less information be more helpful when it comes to making medical decisions? Contrary to the common intuition that more information is always better, the use of heuristics can help both physicians and patients to make sound decisions. Heuristics are simple decision strategies that ignore part of the available information, basing decisions on only a few relevant predictors. We discuss: (i) how doctors and patients use heuristics; and (ii) when heuristics outperform information-greedy methods, such as regressions in medical diagnosis.

Cognitive niches: an ecological model of strategy selection.

How do people select among different strategies to accomplish a given task? Across disciplines, the strategy selection problem represents a major challenge. We propose a quantitative model that predicts how selection emerges through the interplay among strategies, cognitive capacities, and the environment. This interplay carves out for each strategy a cognitive niche, that is, a limited number of situations in which the strategy can be applied, simplifying strategy selection.

From recognition to decisions: extending and testing recognition-based models for multialternative inference.

The recognition heuristic is a noncompensatory strategy for inferring which of two alternatives, one recognized and the other not, scores higher on a criterion. According to it, such inferences are based solely on recognition. We generalize this heuristic to tasks with multiple alternatives, proposing a model of how people identify the consideration sets from which they make their final decisions.

Good judgments do not require complex cognition.

What cognitive capabilities allow Homo sapiens to successfully bet on the stock market, to catch balls in baseball games, to accurately predict the outcomes of political elections, or to correctly decide whether a patient needs to be allocated to the coronary care unit? It is a widespread belief in psychology and beyond that complex judgment tasks require complex solutions. Countering this common intuition, in this article, we argue that in an uncertain world actually the opposite is true: Humans do not need complex cognitive strategies to make good inferences, estimations, and other judgments; rather, it is the very simplicity and robustness of our cognitive repertoire that makes Homo sapiens a capable decision maker.