Philippe Chassy

Expertise and Intuition: A Tale of Three Theories

Several authors have hailed intuition as one of the defining features of expertise. In particular, while disagreeing on almost anything that touches on human cognition and artificial intelligence, Hubert Dreyfus and Herbert Simon agreed on this point. However, the highly influential theories of intuition they proposed differed in major ways, especially with respect to the role given to search and as to whether intuition is holistic or analytic. Both theories suffer from empirical weaknesses. In this paper, we show how, with some additions, a recent theory of expert memory (the template theory) offers a coherent and wide-ranging explanation of intuition in expert behaviour. It is shown that the theory accounts for the key features of intuition: it explains the rapid onset of intuition and its perceptual nature, provides mechanisms for learning, incorporates processes showing how perception is linked to action and emotion, and how experts capture the entirety of a situation. In doing so, the new theory addresses the issues problematic for Dreyfus’s and Simon’s theories. Implications for research and practice are discussed.

Comparison of Quantities: Core and Format-Dependent Regions as Revealed by fMRI

The perception and handling of numbers is central to education. Numerous imaging studies have focused on how quantities are encoded in the brain. Yet, only a few studies have touched upon number mining: the ability to extract the magnitude encoded in a visual stimulus. This article aims to characterize how analogue (i.e., disks and dots) and symbolic (i.e., positive and negative integers) formats influence number mining and the representation of quantities. Sixteen adult volunteers completed a comparison task while we recorded the blood oxygen level-dependent response using functional magnetic resonance imaging. The results revealed that a restricted set of specific subdivisions in the right intraparietal sulcus is activated in all conditions. With respect to magnitude assessment, the results show that 1) analogue stimuli are predominantly processed in the right hemisphere and that 2) symbolic stimuli encompass the analogue system and further recruit areas in the left hemisphere. Crucially, we found that polarity is encoded independently from magnitude. We refine the triple-code model by integrating our findings.

A Hypothesis About the Biological Basis of Expert Intuition

It is well established that intuition plays an important role in experts’ decision making and thinking generally. However, the theories that have been developed at the cognitive level have limits in their explanatory power and lack detailed explanation of the underlying biological mechanisms. In this paper, we bridge this gap by proposing that Hebbs (1949) concept of cell assembly is the biological realization of Simons (1974) concept of chunking. This view provides mechanisms at the biological level that are consistent with both biological and psychological findings. To further address the limits of previous theories, we introduce emotions as a component of intuition by showing how they modulate the perception-memory interaction. The idea that intuition lies at the crossroads between perception, knowledge, and emotional modulation sheds new light on the phenomena of expertise and intuition.

Measuring chess experts' single-use sequence knowledge: An archival study of departure from 'theoretical' openings

The respective roles of knowledge and search have received considerable attention in the literature on expertise. However, most of the evidence on knowledge has been indirect – e.g., by inferring the presence of chunks in long-term memory from performance in memory recall tasks. Here we provide direct estimates of the amount of monochrestic (single use) and rote knowledge held by chess players of varying skill levels. From a large chess database, we analyzed 76,562 games played in 2008 by individuals ranging from Class B players (average players) to Masters to measure the extent to which players deviate from previously known initial sequences of moves (“openings”). Substantial differences were found in the number of moves known by players of different skill levels, with more expert players knowing more moves. Combined with assumptions independently made about the branching factor in master games, we estimate that masters have memorized about 100,000 opening moves. Our results support the hypothesis that monochrestic knowledge is essential for reaching high levels of expertise in chess. They provide a direct, quantitative estimate of the number of opening moves that players have to know to reach master level.

A Comparative Study of Six Formal Models of Causal Ascription

Ascribing causality amounts to determining what elements in a sequence of reported facts can be related in a causal way, on the basis of some knowledge about the course of the world. The paper offers a comparison of a large span of formal models (based on structural equations, non-monotonic consequence relations, trajectory preference relations, identification of violated norms, graphical representations, or connectionism), using a running example taken from a corpus of car accident reports. Interestingly enough, the compared approaches focus on different aspects of the problem by either identifying all the potential causes, or selecting a smaller subset by taking advantages of contextually abnormal facts, or by modeling interventions to get rid of simple correlations. The paper concludes by a general discussion based on a battery of criteria (several of them being proper to AI approaches to causality).

Season of birth and chess expertise.

The origin of talent and expertise is currently the subject of intense debate, with explanations ranging from purely biological to purely environmental. This report shows that the population of expert chess players in the northern hemisphere shows a seasonal pattern, with an excess of births in late winter and early spring. This effect remains when taking into account the distribution of births in the population at large, using statistics from the European Union member countries. A similar pattern has been found with schizophrenia, and the possible link between these two phenomena is discussed.

Risk taking in adversarial situations: Civilization differences in chess experts

The projections of experts in politics predict that a new world order will emerge within two decades. Being multipolar, this world will inevitably lead to frictions where civilizations and states will have to decide whether to risk conflict. Very often these decisions are informed if not taken by experts. To estimate risk-taking across civilizations, we examined strategies used in 667,599 chess games played over eleven years by chess experts from 11 different civilizations. We show that some civilizations are more inclined to settle for peace. Similarly, we show that once engaged in the battle, the level of risk taking varies significantly across civilizations, the boldest civilization using the riskiest strategy about 35% more than the most conservative civilization. We discuss which psychological factors might underpin these civilizational differences.

The Role of Memory Templates in Experts＇ Strategic Thinking

There is ample evidence that experts’ performance is mostly due to domain specific knowledge. Some complex memory structures, termed templates, have been theorised to underpin strategic thinking in expert chess players. A behavioural study and computer simulations have been used to test this hypothesis. The behavioural study is the first to show that experts identify strategic systems with more accuracy than novices do. A new artificial neural network model is introduced to implement visuospatial templates. The simulations indicate that templates adequately model identification of strategies in novice and expert players. Both results support the view that templates underpin strategic thinking. The findings constitute a demonstration of the dependence of strategic thinking on memory processes and open the door for a new theoretical approach to understand high-level cognition.

A Relationship Between Visual Complexity and Aesthetic Appraisal of Car Front Images: An Eye-Tracker Study.

Image aesthetic pleasure (AP) is conjectured to be related to image visual complexity (VC). The aim of the present study was to investigate whether (a) two image attributes, AP and VC, are reflected in eye-movement parameters; and (b) subjective measures of AP and VC are related. Participants (N = 26) explored car front images (M = 50) while their eye movements were recorded. Following image exposure (10 seconds), its VC and AP were rated. Fixation count was found to positively correlate with the subjective VC and its objective proxy, JPEG compression size, suggesting that this eye-movement parameter can be considered an objective behavioral measure of VC. AP, in comparison, positively correlated with average dwelling time. Subjective measures of AP and VC were related too, following an inverted U-shape function best-fit by a quadratic equation. In addition, AP was found to be modulated by car prestige. Our findings reveal a close relationship between subjective and objective measures of complexity and aesthetic appraisal, which is interpreted within a prototype-based theory framework.

Making sense as a process emerging from perception–memory interaction: A model

Making sense is a goal‐driven process that integrates perceptual input into a cohesive internal representation. For human agents, it plays a central role in causal ascription or responsibility assignment. In this paper, we outline a theory of making sense. Making sense is hypothesized to arise from the interaction between perceptual input and context‐dependent knowledge that was activated in long‐term memory. Accordingly, the model draws heavily on psychological findings related to memory processing. The psychological grounding is completed by knowledge about cognitive architecture and supplemented by the literature on the attribution of cause and responsibility. The evidence is then integrated in an artificial intelligence (AI) model of making sense. The formalism and the mechanisms are inspired from previous AI research on causal ascription. We present a detailed account of the computer implementation. The implementation makes clear how knowledge influences the process of making sense in agreement with the psychological assumptions underlying the formal model.