Sources of difficulty in insight problem-solving have been identified, but current theories are less successful at explaining discovery of solution ideas. Here, we explore the role of expertise in promoting insight. In Experiment 1, experienced designers and financiers solved visual and verbal problems. Expertise did not influence solution rates for verbal problems, but designers solved more visual problems than financiers, despite similar incorrect initial attempts. In Experiment 2, experienced and novice designers attempted problems either unconstrained, prevented from drawing, or sitting (...) on their hands to prevent drawing and gesture. Hand and drawing constraints removed the positive benefits of expertise. Experienced designers appear to solve visual problems by using strategies to explore the visuo-spatial environment in search of new representations. The results indicate that expert strategic knowledge can be a source of insight. They also show that strategic transfer of expertise to far domains can be achieved. (shrink)

One hundred and three participants solved conflict and non-conflict versions of four reasoning tasks using a two-response procedure: a base rate task, a causal reasoning task, a denominator neglect task, and a categorical syllogisms task. Participants were asked to give their first, intuitive answer, to make a Feeling of Rightness judgment, and then were given as much time as needed to rethink their answer. They also completed a standardized measure of IQ and the actively open-minded thinking questionnaire. The FORs of (...) both high- and low-capacity reasoners were responsive to conflict, such that FORs were lower for conflict relative to non-conflict problems. Consistent with the quantity hypothesis, high-capacity reasoners made a greater distinction between conflict and non-conflict items on measures of Type 2 thinking, namely, rethinking time and probability of changing answers. In contrast to the quality hypothesis, however, this rethinking time did not advantage the ability of the high-capacity group to produce normative answers, except for the base rate task. Indeed, we observed that the correlation between capacity and the probability of normative answers emerged at the initial response, rather than after rethinking. (shrink)

Many kinds of creativity result from combination of mental representations. This paper provides a computational account of how creative thinking can arise from combining neural patterns into ones that are potentially novel and useful. We defend the hypothesis that such combinations arise from mechanisms that bind together neural activity by a process of convolution, a mathematical operation that interweaves structures. We describe computer simulations that show the feasibility of using convolution to produce emergent patterns of neural activity that can support (...) cognitive and emotional processes underlying human creativity. (shrink)

The goal of this research is to explore implicit and explicit processes in shaping an individual’s characteristic behavioral patterns, that is, personality. The questions addressed are how psychological processes may be separated into implicit and explicit types, and how such a separation figures into personality. In particular, it focuses on the role of instinct and intuition in determining personality. This paper argues that personality may be fundamentally based on instincts resulting from basic human motivation, along with related processes, within a (...) comprehensive cognitive architecture. This approach is implemented as a computational model. Various tests and simulations show that this model captures major personality traits and accounts for empirical data. The work shows how a cognitive architecture with the implicit–explicit distinction may capture instinct, intuition, and personality. (shrink)

It is highly likely that, to achieve full human–machine symbiosis, truly intelligent cognitive systems—human-like —may have to be developed first. Such systems should not only be capable of performing human-like thinking, reasoning, and problem solving, but also be capable of displaying human-like motivation, emotion, and personality. In this opinion article, I will argue that such systems are indeed possible and needed to achieve true and full symbiosis with humans. A computational cognitive architecture is used in this article to illustrate, in (...) a preliminary way, what can be achieved in this regard. It is shown that Clarion involves complex structures, representations, and mechanisms, and is capable of capturing human cognitive performance as well as human motivation, emotion, personality, and other relevant aspects. It is further argued that the cognitive architecture can enable and facilitate true human–machine symbiosis. (shrink)

This paper explores an approach for autonomous generation of symbolic representations from an agent's subsymbolic activities within the agent-environment interaction. The paper describes a psychologically plausible general framework and its various methods for autonomously creating symbolic representations. The symbol generation is accomplished within, and is intrinsic to, a generic and comprehensive cognitive architecture for capturing a wide variety of psychological processes (namely, CLARION). This work points to ways of obtaining more psychologically/cognitively realistic symbolic and subsymbolic representations within the framework of (...) a cognitive architecture, and accentuates the relevance of such an approach to cognitive science and psychology. (shrink)

Evidence for incubation effects in problem-solving is increasing, but the mechanisms that underlie incubation are unclear. An experiment tested two hypotheses about incubation: Spreading activation and opportunistic assimilation. Participants solved easy or difficult remote associates tasks without incubation period, or with an incubation period filled with high or low cognitive load tasks. A lexical decision task with cue and neutral words was given either before or after a second problem attempt. When solving difficult problems, the low-load incubation group benefitted more (...) from the presence of a cue than the high-load incubation group, and the opposite was found with easy problems. Neither incubation nor an initial problem attempt affected lexical decision times to cue words. The results favour opportunistic assimilation as an explanation of incubation effects. They also suggest a differential role for attentional allocation depending on problem difficulty, easy problems benefitting from focused attent.. (shrink)

This article compares the information processing and dynamical systems perspectives on problem solving. Key theoretical constructs of the information-processing perspective include “searching” a “p...

The study of insight problem solving could well become one of the most important topics in the contemporary debate on thought. Dealing with insight problems today requires of necessity reconsidering the concept of bounded rationality. Simon’s work has inspired us to reflect on the specific quality of the type of boundaries which, by limiting the search, allow and guarantee the act of creativity; finding the solution to insight problems is emblematic of this creativity and provides a paradigmatic case. According to (...) Simon, the solution to insight problems requires a search for an alternative space. He considered the “Notice Invariants Heuristic” to be a powerful tool for focusing this search which must always be guided by salience. Therefore, in the case of insight problems the heuristic is not a weak method of solving problems; indeed, it is the only way, an innovative and creative approach to reach the solution. In our view, the solution to these problems is not attained by abstraction, but only by a pertinent interpretation of the context (interpretative heuristic) in the light of the goal, allowing the problem solver to abandon the default representation. We therefore propose that this interpretative heuristic is inherent to all insight problem solving processes and, in more general terms, is an adaptive characteristic of the human cognitive system; this of course implies that the dual process theory will have to be challenged and discussed. (shrink)

The article proposes a universal dual-axis intelligent systems assessment scale. The scale considers the properties of intelligent systems within the environmental context, which develops over time. In contrast to the frequent consideration of the “mind” of artificial intelligent systems on a scale from “weak” to “strong”, we highlight the modulating influences of anticipatory ability on their “brute force”. In addition, the complexity, the ”weight“ of the cognitive task and the ability to critically assess it beforehand determine the actual set of (...) cognitive tools, the use of which provides the best result in these conditions. In fact, the presence of ”common sense“ options is what connects the ability to solve a problem with the correct use of such an ability itself. The degree of ”correctness“ and ”adequacy“ is determined by the combination of a suitable solution with the temporal characteristics of the event, phenomenon, object or subject under study. The proposed approach can be applied in the evaluation of various intelligent agents in different contexts including AI and humans performing complex domain-specific tasks with high uncertainty. (shrink)

A problem is a situation in which an agent seeks to attain a given goal without knowing how to achieve it. Human problem solving is typically studied as a search in a problem space composed of states (information about the environment) and operators (to move between states). A problem such as playing a game of chess has possible states, and a traveling salesperson problem with as little as 82 cities already has more than different tours (similar to chess). Biological neurons (...) are slower than the digital switches in computers. An exhaustive search of the problem space exceeds the capacity of current computers for most interesting problems, and it is fairly clear that humans cannot in their lifetime exhaustively search even small fractions of these problem spaces. Yet, humans play chess and solve logistical problems of similar complexity on a daily basis. Even for simple problems humans do not typically engage in exploring even a small fraction of the problem space. This begs the question: How do humans solve problems on a daily basis in a fast and efficient way? Recent work suggests that humans build a problem representation and solve the represented problem—not the problem that is out there. The problem representation that is built and the process used to solve it are constrained by limits of cognitive capacity and a cost–benefit analysis discounting effort and reward. In this article, we argue that better understanding the way humans represent and solve problems using heuristics can help inform how simpler algorithms and representations can be used in artificial intelligence to lower computational complexity, reduce computation time, and facilitate real-time computation in complex problem solving. (shrink)

Pour la plupart des systèmes de représentation de la connaissance orientés concept, l’un des problèmes principaux relève de la commodité technique. A savoir, la représentation de connaissance en termes prototypiques, tout comme la possibilité d’exploiter des formes de raisonnement conceptuel basées sur la typicalité, ne sont pas autorisées. Au contraire, dans les sciences cognitives, il existe des données en faveur de concepts prototypiques, et des formes non-monotoniques de raisonnement conceptuel ont été largement étudiées. Ce fossé cognitif concernant la représentation et (...) le raisonnement constitue un problème pour les systèmes computationnels, puisque l’information prototypique joue un rôle crucial dans plusieurs tâches importantes. Dans la lignée des théories du raisonnement et de la rationalité dites du double processus, nous soutenons que la représentation conceptuelle dans les systèmes computationnels devrait dépendre de deux composantes représentationnelles, chacune spécialisée dans le traitement de différents genres de processus de raisonnement. Dans cet article, nous présentons les avantages computationnels de cette approche en termes de double processus, et les comparons brièvement avec d’autres solutions d’orientation logique, adoptées pour traiter du même problème. (shrink)

Pour la plupart des systèmes de représentation de la connaissance orientés concept, l’un des problèmes principaux relève de la commodité technique. A savoir, la représentation de connaissance en termes prototypiques, tout comme la possibilité d’exploiter des formes de raisonnement conceptuel basées sur la typicalité, ne sont pas autorisées. Au contraire, dans les sciences cognitives, il existe des données en faveur de concepts prototypiques, et des formes non-monotoniques de raisonnement conceptuel ont été largement étudiées. Ce fossé cognitif concernant la représentation et (...) le raisonnement constitue un problème pour les systèmes computationnels, puisque l’information prototypique joue un rôle crucial dans plusieurs tâches importantes. Dans la lignée des théories du raisonnement et de la rationalité dites du double processus, nous soutenons que la représentation conceptuelle dans les systèmes computationnels devrait dépendre de (au moins) deux composantes représentationnelles, chacune spécialisée dans le traitement de différents genres de processus de raisonnement. Dans cet article, nous présentons les avantages computationnels de cette approche en termes de double processus, et les comparons brièvement avec d’autres solutions d’orientation logique, adoptées pour traiter du même problème. (shrink)

ABSTRACTInitial acts of self-control can reduce effort and performance on subsequent tasks – a phenomenon known as ego depletion. Ego depletion is thought to undermine the capacity or willingness to engage executive control, an important determinant of success for many tasks. We examined whether ego depletion improves performance on a task that favours less executive control: insight problem solving. In two experiments, participants completed an ego-depletion manipulation or a non-depleting control condition followed by an insight problem-solving task. Participants in the (...) depleting condition demonstrated greater insight problem-solving accuracy than those in the non-depleting control condition. Priming theories of willpower did not impact these results. Although ego depletion is widely regarded as a “state of impairment”, attendant decreases in executive control may foster insightful thinking. (shrink)

Insight often strikes us blind; when we aren’t expecting it, we suddenly see a connection that previously eluded us—a kind of ‘Aha!’ experience. People with a propensity to such experiences are regarded as insightful, and insightfulness is a paradigmatic intellectual virtue. What’s not clear, however, is just what it is in virtue of which being such that these experiences tend to happen to one renders one intellectually virtuous. This paper draws from both virtue epistemology as well as empirical work on (...) the psychology of problem solving and creativity to make some inroads in accounting for insightfulness as an intellectual virtue. Important to the view advanced is that virtuously insightful individuals manifest certain skills which both cultivate insight experiences (even if not by directly bringing them about) and enable such individuals to move in an epistemically responsible way from insight experience to epistemic endorsement. (shrink)

This paper explores the effect of different types of incubation task (visual, numerical and verbal) with various levels of attentional focus and cognitive effort (non-demanding, low-demanding and high-demanding) on the resolution of insight problems. The most effective was found to be the low-demanding task (regardless of its nature), which although requiring attentional focus, leaves resources available for the unconscious analytical restructuring process, obtaining a high percentage of success in solving the problem shortly after completion of the incubation task. Overall findings (...) support the hypothesis of Unconscious Analytic Thought (UAT), according to which the restructuring required in insight problem solving implies a covert thinking process that includes a relevant, analytic and goal-oriented search. The findings are discussed in the light of UAT and are compared with the main theories of insight in problem solving. (shrink)

Paradoxes are an unavoidable part of work life. The unusualness of attempting to simultaneously satisfy contradictory imperatives can result in creative outcomes that simultaneously satisfy both imperatives by inducing search for, and selection of, novel and useful solutions. Likewise, extant research suggests that paradoxes can also result in anxiety, defensiveness, and persistence of old ways of doing things. However, there is little work attempting to describe how paradoxes affect cognition and when it results in higher or lower creativity. To tackle (...) this issue, a theory of paradoxical creativity is developed. Paradoxical creativity is the attempt by an individual to creatively resolve a contradiction by simultaneously achieving competing demands. The theory is implemented into a computational model and a simulation is used to describe how paradoxes affect creative cognitive process and how these processes in turn result in higher or lower degrees of creativity. The results show that creative output is enhanced when paradoxes have a balanced effect on the cognitive processes responsible for an individual’s capacity to search for new information and willingness to tolerate new ideas. Hence, individuals with high baseline levels of creative cognition are more likely to suffer negative creative performance consequences resulting from contradictory demands. For those individuals, contradictory demands may produce more alternatives, which increases uncertainty and time to insight (if insight is ever reached). This suggests that incentives or rewards to resolve contradictions may have the unintentional effect of reducing creative output in some circumstance. (shrink)

This paper compares two theories and their two corresponding computational models of human moral judgment. In order to better address psychological realism and generality of theories of moral judgment, more detailed and more psychologically nuanced models are needed. In particular, a motivationally based theory of moral judgment is developed in this paper that provides a more accurate account of human moral judgment than an existing emotion-reason conflict theory. Simulations based on the theory capture and explain a range of relevant human (...) data. They account not only for the original data that were used to support the emotion–reason conflict theory, but also for a wider range of data and phenomena. (shrink)