Political scientists have proposed that party cues can be used to compensate for the public's well-documented lack of substantive political knowledge, but some critics have argued that applying party cues is more difficult than assumed. We argue that this debate has proven intractable in part because scholars have used ambiguous normative criteria to evaluate judgments. We use a unique task and clear normative criteria to evaluate the use of party cues in making political judgments among two samples: a sample of state legislators and an online sample of the public. We find that the public sample performs poorly when using cues to make judgments. State legislators make much more accurate judgments on average than even the most attentive segment of the public and are more likely to place less weight on irrelevant cues when making judgments, although there is evidence that both samples performed worse with the inclusion of non-diagnostic cues. We conclude with a discussion of the relevance of the results, which we interpret as showing that party cue use is more difficult than theorized, and discuss some practical implications of the findings.

Ad hoc teamwork (AHT) refers to the problem of enabling an agent to collaborate with teammates without prior coordination. State of the art methods in AHT are data-driven, using a large labeled dataset of prior observations to model the behavior of other agent types and to determine the ad hoc agent’s behavior. These methods are computationally expensive, lack transparency, and make it difficult to adapt to previously unseen changes. Our recent work introduced an architecture that determined an ad hoc agent’s behavior based on non-monotonic logical reasoning with prior commonsense domain knowledge and models learned from limited examples to predict the behavior of other agents. This paper describes KAT, a knowledge-driven architecture for AHT that substantially expands our prior architecture’s capabilities to support: (a) online selection, adaptation, and learning of the behavior prediction models; and (b) collaboration with teammates in the presence of partial observability and limited communication. We illustrate and experimentally evaluate KAT’s capabilities in two simulated benchmark domains for multiagent collaboration: Fort Attack and Half Field Offense. We show that KAT’s performance is better than a purely knowledge-driven baseline, and comparable with or better than a state of the art data-driven baseline, particularly in the presence of limited training data, partial observability, and changes in team composition.

How do mushroom foragers make safe and efficient decisions under uncertainty, or deal with the genuine risks of misidentification and poisoning? This article is an inquiry into ecological rationality, heuristics, perception, and decision-making in mushroom foraging. By surveying 894 Finnish mushroom foragers, this article illustrates how socially learned rules of thumb and heuristics are used in mushroom foraging, and how simple heuristics are often complemented by more complex and intuitive decision-making. The results illustrate how traditional foraging cultures have evolved precautionary heuristics to deal with uncertainties and poisonous species, and how foragers develop selective attention through experience. The study invites us to consider whether other human foraging cultures might use heuristics similarly, how and why such traditions have culturally evolved, and whether early hunter-gatherers might have used simple heuristics to deal with uncertainty.

The recognition heuristic exploits the basic psychological capacity for recognition in order to make inferences about unknown quantities in the world. In this article, we review and clarify issues that emerged from our initial work (Goldstein & Gigerenzer, 1999, 2002), including the distinction between a recognition and an evaluation process. There is now considerable evidence that (i) the recognition heuristic predicts the inferences of a substantial proportion of individuals consistently, even in the presence of one or more contradicting cues, (ii) people are adaptive decision makers in that accordance increases with larger recognition validity and decreases in situations when the validity is low or wholly indeterminable, and (iii) in the presence of contradicting cues, some individuals appear to select different strategies. Little is known about these individual differences, or how to precisely model the alternative strategies. Although some researchers have attributed judgments inconsistent with the use of the recognition heuristic to compensatory processing, little research on such compensatory models has been reported. We discuss extensions of the recognition model, open questions, unanticipated results, and the surprising predictive power of recognition in forecasting.

The diversity, ingenuity and differences of opinion displayed in the articles of the recent special issues on the recognition heuristic are testament to the power and theoretical fertility of a simple idea about the role of recognition in decision making. In this brief comment I mention a number of these papers, but my focus is on points of agreement and disagreement with the conclusions drawn by Gigerenzer and Goldstein (2011) in their review of a decade’s worth of research on the recognition heuristic.

Contrary to the common belief that more information is always better, Gigerenzer et al. (1999) showed that simple decision strategies which rely on little information can be quite successful. The success of simple strategies depends both on bets about the structure of the environment and on the core capacities of the human mind, such as recognition memory (Gigerenzer, 2004). However, the interplay between the environment and the mind’s core capacities has rarely been precisely modeled. We illustrate how these environment-mind interactions could be formally modeled within the cognitive architecture ACT-R (J. R. Anderson et al., 2004). ACT-R is an integrated theory of mind that is tuned to the statistical structure of the environment, and it can account for a variety of phenomena such as learning, problem solving, and decision making. Here, we focus on studying decision strategies and show how the success of theses strategies in particular environments depends on characteristics of core cognitive capacities, such as recognition and short term memory.

Marketing science seeks to prescribe better marketing strategies (advertising, product development, pricing, etc.). To do so we rely on models of consumer decisions grounded in empirical observations. Field experience suggests that recognition-based heuristics help consumers to choose which brands to consider and purchase in frequently-purchased categories, but other heuristics are more relevant in durable-goods categories. Screening with recognition is a rational screening rule when advertising is a signal of product quality, when observing other consumers makes it easy to learn decision rules, and when firms react to engineering-design constraints by offering brands such that a high-level on one product feature implies a low level on another product feature. Experience with applications and field experiments suggests four fruitful research topics: deciding how to decide (endogeneity), learning decision rules by self-reflection, risk reduction, and the difference between utility functions and decision rules. These challenges also pose methodological cautions.

The recognition heuristic models the adaptive use and dominant role of recognition knowledge in judgment under uncertainty. Of the several predictions that the heuristic makes, empirical tests have predominantly focused on the proposed noncompensatory processing of recognition. Some authors have emphasized that the heuristic needs to be scrutinized based on precise tests of the exclusive use of recognition. Although precise tests have clear merits, I critically evaluate the value of such tests as they are currently employed. First, I argue that using precise measures of the exclusive use of recognition has to go beyond showing that the recognition heuristic—like every model—cannot capture reality completely. Second, I illustrate how precise tests based on response times can lead to unsubstantiated conclusions if the fact that the recognition heuristic does not model the recognition judgment itself is ignored. Finally, I highlight two key but so far neglected aspects of the recognition heuristic: (a) the connection between recognition memory and the recognition heuristic; and (b) the mechanisms underlying the adaptive use of recognition.

This paper discusses a research agenda for post-Northian institutional economics, which focuses on economic cognitive institutions and minds–institutions interactions. Douglass North introduced the ‘shared mental models’ and ‘shared beliefs’ concepts, which were considered the cutting edge of cognitive science at that time, the so-called first wave of extended mind theory. Subsequently, two more waves arose, but they went unnoticed by institutional economists who mostly continue to use internalist and reductionist approaches to cognition. Post-Northian institutional economics offers a deeper understanding of the relationship between cognition and institutions in the spirit of third-wave extended mind theory. The research agenda emphasizes a focus on socially extended cognition and the conception of cognitive institutions as shared mental processes (Petracca and Gallagher, 2020). I propose an alternative definition of cognitive institutions as interactively and polycentrically co-produced cognitive norms; this approach highlights normativity, co-production, and distributed active agency in extended cognitive processes. I propose two domains in which this third-wave framework can be used: ecological rationality and cognitive–cultural niche construction. This paper encourages a discussion on the prospects of a third-wave enactivist turn in institutional economics.

This paper compares the key arguments of ecological modernization theory (EMT) with the reality of recent environmental reform in China. Based on data gathered from a survey and in-depth interviews with executives from Hong Kong-based enterprises operating in Guangdong province, we examine the changing roles of government, market, and civil society actors in the reform process, focusing on various types of pressures these actors have exerted on business enterprises. Compatible with Mol's (2006) conjectures, ecological concerns have gradually gained a foothold in existing political, economic, and to a lesser extent, social institutions. Yet, the relevant actors and their patterns of interactions differ from what EMT generalizes from Western European experiences. Specifically, local governments are assuming a more formalized relationship with firms in regulatory enforcement. Among market actors, organizational buyers along the supply chain have exerted more noticeable pressures on manufacturing firms than industrial associations and individual consumers. Civil society, while remaining less of an institutionalized actor in the environmental policy process, appears to pose a perceptible threat to at least some firms.