From artistic performances in the visual arts and in music to motor control in gymnastics, from tool use to chess and language, humans excel in a variety of skills. On the plausible assumption that skillful behavior is a visible manifestation of intelligence, a theory of intelligence—whether human or not—should be informed by a theory of skills. More controversial is the question as to whether, in order to theorize about intelligence, we should study certain skills in particular. My target is the (...) view that only a particular class/kind of skill (i.e., ‘theoretical’, or ‘intellectual’ skills, versus ‘practical’, or ‘embodied’ skills) manifests intelligence, or especially does so. I call this view ‘Intelligence Elitism’. Intelligence Elitism is pervasive in popular culture, in academic culture, as well as in psychometrics. It has, arguably, a long pedigree in philosophy (though explicit arguments for it are rare). But it is a substantive view which, if false, can promote unfairness. In this article, I defend Intelligence Socialism—the claim that intelligent behavior is everywhere skillful behavior is. I go on to isolate the best case for the further Elitist claim that, even if all skillful behavior is intelligent in some modest sense of ‘intelligence’, there is a principled difference in intelligence between theoretical, or intellectual, skills, on one side, and practical, or embodied skills, on the other, and I show it wanting. (shrink)

The recent upsurge in “brain-training and perceptual-cognitive-training", proposing to improve isolated processes such as brain function, visual perception and decision-making, has created significant interest in elite sports practitioners, seeking to create an ‘edge’ for athletes. The claims of these related 'performance-enhancing industries' can be considered together as part of a process training approach proposing enhanced cognitive and perceptual skills and brain capacity, to support performance in everyday life activities, including sport. For example, the 'process-training industry' promotes the idea that playing (...) games not only makes you a better player, but also smarter, more alert, and a faster learner. In this position paper we critically evaluate the effectiveness of both types of process-training programmes in generalizing transfer to sport performance. These issues are addressed in three stages. First, we evaluate empirical evidence in support of perceptual-cognitive process training, and its application to enhancing sport performance. Second, we critically review putative modularised mechanisms underpinning this kind of training, addressing limitations and subsequent problems. Specifically, we consider merits of this highly specific form of training, which focuses on training of isolated processes such as cognitive processes (attention, memory, thinking) and visual perception processes, separately from performance behaviors and actions. We conclude that these approaches may, at best, may provide some 'general transfer' of underlying processes to specific sport environments, but lack 'specificity of transfer' to contextualize actual performance behaviors. A major weakness of process training methods is their focus on enhancing performance in body “modules” (e.g., eye, brain, memory, anticipatory sub-systems). What is lacking is evidence on how these isolated components are modified and subsequently interact with other process “modules”, which are considered to underlie sport performance. Finally, we propose how an ecological dynamics approach, aligned with an embodied framework of cognition undermines the rationale that modularised processes can enhance performance in competitive sport. An ecological dynamics perspective proposes that the body is a complex adaptive system, interacting with performance environments in a functionally integrated manner, emphasising that the inter-relation between motor processes, cognitive and perceptual functions and the constraints of a sport task is best understood at the performer-environment scale of analysis. (shrink)

How do people reason about their opponent in turn-taking games? Often, people do not make the decisions that game theory would prescribe. We present a logic that can play a key role in understanding how people make their decisions, by delineating all plausible reasoning strategies in a systematic manner. This in turn makes it possible to construct a corresponding set of computational models in a cognitive architecture. These models can be run and fitted to the participants’ data in terms of (...) decisions, response times, and answers to questions. We validate these claims on the basis of an earlier game-theoretic experiment about the turn-taking game “Marble Drop with Surprising Opponent”, in which the opponent often starts with a seemingly irrational move. We explore two ways of segregating the participants into reasonable “player types”. The first way is based on latent class analysis, which divides the players into three classes according to their first decisions in the game: Random players, Learners, and Expected players, who make decisions consistent with forward induction. The second way is based on participants’ answers to a question about their opponent, classified according to levels of theory of mind: zero-order, first-order and second-order. It turns out that increasing levels of decisions and theory of mind both correspond to increasing success as measured by monetary awards and increasing decision times. Next, we use the logical language to express different kinds of strategies that people apply when reasoning about their opponent and making decisions in turn-taking games, as well as the ‘reasoning types’ reflected in their behavior. Then, we translate the logical formulas into computational cognitive models in the PRIMs architecture. Finally, we run two of the resulting models, corresponding to the strategy of only being interested in one’s own payoff and to the myopic strategy, in which one can only look ahead to a limited number of nodes. It turns out that the participant data fit to the own-payoff strategy, not the myopic one. The article closes the circle from experiments via logic and cognitive modelling back to predictions about new experiments. (shrink)

Mental actions are things we do with our minds. Consider inferring, deliberating, imagining, remembering, calculating, and so on. I introduce a non-reductive alternative to standard causalist accounts of mental action that understands such action in terms of dispositions for performing mental actions. I call this alternative the powers framework. On the powers framework, habitual and skillful mental actions are themselves infused with practical intelligence by being expressions of the agent’s rational tendencies and capacities, respectively. The intelligence exemplified in the performance (...) of habitual and skillful mental actions stems from the agent’s having shaped the corresponding tendencies and capacities through training and practice. In this way, mental habits and skills are ‘second nature’ to us. I substantiate the powers framework by giving an account of imagining as a type of skillful mental action. In particular, I argue that imagination is a power to construct representations and select their contents as a means to performing learned behaviors like pretending, engaging with fiction, predicting others’ behavior, reasoning about possibility and necessity, reasoning hypothetically or counterfactually about contingent matters of fact, and even imagining for its own sake. I extend the account of imagining to episodic remembering. I argue that such remembering, considered as a mental action, is a kind of imagining by virtue of the agent’s constructing a representation and selecting its content as a means of performing the learned behavior of navigating her personal past. (shrink)

People can learn to perform new tasks very quickly by making use of lower‐level skills they have developed when learning previous tasks. Hoekstra, Martens, and Taatgen model this process, showing how a system trained on simple tasks (visual search and two working memory tasks) can then quickly learn to perform the attentional blink task, and it ends up making the same sorts of errors as people do.

Impairments in executive functioning are prevalent in chronic pain conditions, with cognitive inflexibility being the most frequently reported. The current randomized, cross-over trial, piloted a computerized cognitive training program based on Relational Frame Theory, targeting improvement in cognitive flexibility. At baseline, 73 chronic pain patients completed testing on pre-selected outcomes of executive functioning, alongside IQ measures. When tested three times over the course of 5 months, there was a drop-out rate of 40% at the third time point, leaving 44 patients (...) who had data at all time points. The results showed that there was a substantial learning effect from the MINDFLEX training and a substantial time-dependent improvement on the primary outcomes of increased flexibility, but that this could not be tied to active training. In conclusion, this small study indicated a learning effect as well as improvement on primary outcomes. Based on the current results, a larger trial with improved feasibility of training is warranted. (shrink)

The ability to reason and problem‐solve in novel situations, as measured by the Raven's Advanced Progressive Matrices (RAPM), is highly predictive of both cognitive task performance and real‐world outcomes. Here we provide evidence that RAPM performance depends on the ability to reallocate attention in response to self‐generated feedback about progress. We propose that such an ability is underpinned by the basal ganglia nuclei, which are critically tied to both reward processing and cognitive control. This hypothesis was implemented in a neurocomputational (...) model of the RAPM task, which was used to derive novel predictions at the behavioral and neural levels. These predictions were then verified in one neuroimaging and two behavioral experiments. Furthermore, an effective connectivity analysis of the neuroimaging data confirmed a role for the basal ganglia in modulating attention. Taken together, these results suggest that individual differences in a neural circuit related to reward processing underpin human fluid reasoning abilities. (shrink)

The goal of cognitive modeling is to build faithful simulations of human cognition. One of the challenges is that multiple models can often explain the same phenomena. Another challenge is that models are often very hard to understand, explore, and reuse by others. We discuss some of the solutions that were discussed during the 2015 International Conference on Cognitive Modeling.

The goal of cognitive modeling is to build faithful simulations of human cognition. One of the challenges is that multiple models can often explain the same phenomena. Another challenge is that models are often very hard to understand, explore, and reuse by others. We discuss some of the solutions that were discussed during the 2015 International Conference on Cognitive Modeling.

Maintaining and coordinating multiple task-sets is difficult and leads to costs, however task-switching training can reduce these deficits. A recent study in young adults demonstrated that this training effect occurs at an amodal processing level. Old age is associated with reduced cognitive plasticity and further increases the performance costs when mixing multiple tasks. Thus, cognitive aging might be a limiting factor for inducing cross-modal training effects in a task-switching environment. We trained participants, aged 62–83 years, with an auditory task-switching paradigm (...) over four sessions, to investigate whether training-related reductions in task-switching costs would also manifest in an untrained visual modality version of the task. Two control groups trained with single tasks or not trained allowed us to identify improvements specific to task-switching training. To make statistical evaluations of any age differences in training and cross-modal transfer, the data from the Kattner cohort were incorporated into the present analysis. Despite the tendency for older adults to respond more cautiously, task-switching training specifically led to a mixing cost reduction in both trained and untrained modalities, the magnitude of which was statistically similar regardless of age. In line with a growing body of research, we failed to observe any far transfer effects in measures of inhibition, working memory or fluid intelligence. Overall, we conclude that any apparent cognitive limitations associated with aging do not prevent cognitive control processes which support set-shifting from improving at an amodal level. (shrink)