La tesis aborda uno de los temas centrales en la filosofía de la mente y las ciencias cognitivas: los conceptos como unidades básicas de la cognición humana. La tesis central que se defiende es que el contenido de los conceptos es determinado parcialmente por las comunidades a las que pertenecen los sujetos cognitivos, en la medida en la que dichas comunidades guían y constriñen las interacciones entre el sistema cognitivo conceptual y el entorno del que forma conceptos. La novedad de (...) la tesis es doble. Por una parte, cuestiona las teorías dominantes sobre el contenido de los conceptos —las teorías descriptivistas y las teorías naturalistas—, no solamente a partir de desafíos filosóficos que muestran sus limitaciones, sino también a partir de evidencia empírica sobre el efecto de las interacciones sociales en el contenido de los conceptos y, por tanto, en la cognición. Por otra parte, proporciona evidencia empírica sobre infantes ferales (i.e. niños salvajes), cuyo sistema cognitivo conceptual no ha recibido la guía de ninguna comunidad humana en sus interacciones con el entorno. Dicha evidencia permite sugerir que una explicación puramente naturalizada del contenido, sin la presencia de las comunidades, no puede explicar el desarrollo cognitivo conceptual de dichos infantes. Así, la tesis logra proponer un papel no trivial de las comunidades en el debate sobre la determinación del contenido semántico de los conceptos. (shrink)

What the Sorites has to tell us is a simple truth regarding our categories. It appears to saddle us with something other than a simple truth—something worse, a contradiction or a problem or a paradox—only when we insist on viewing it through a discrete logic of categories. Discrete categories and discrete logic are for robots. We aren’t robots, and the simple truth is that we don’t handle categories in the way any discrete logic would demand. For us non-robots, what the (...) Sorites has to offer is a straightforward truth regarding how incapable robots and their logic are of handling categories like ours. (shrink)

This original research hypothesises that the most fundamental building blocks of logical descriptions of cognitive, or knowledge, agents’ descriptions are expressible based on their conceptions (of the world). This article conceptually and logically analyses agents’ conceptions in order to offer a constructivist- based logical model for terminological knowledge. The most significant characteristic of [terminological] knowing is that there are strong interrelationships between terminological knowledge and the individualistic constructed, and to-be-constructed, models of knowledge. Correspondingly, I conceptually and logically analyse conception expressions (...) based on terminological knowledge, and I show how terminological knowledge may reasonably be assumed to be constructed based on the agents’ conceptions of the world. The focus of my model is on terminological knowledge structures, which may find applications in such diverse fields as the Semantic Web and educational/learning systems. (shrink)

Concept formation is a crucial milestone for cognitive development. In the last 40 years, empirical evidence obtained in laboratory settings suggested that babies have a rich conceptual system that expresses in responses to stimuli. However, very little is still known about how concepts develop in every day, ecological contexts. This is due to a lack of studies addressing (i) the intersubjective contexts of activity in which concepts develop and (ii) the meanings that objects that are part of those contexts acquire (...) through material engagement. This paper presents a qualitative analysis of six observations from a longitudinal pilot study carried out at an infant school in Madrid (Spain), with children from ages 5 to 17 months. Children’s interactions with each other, with their teacher, and with objects were recorded every 21 days for 6 months. Results show that when children, in their first year of life, grasp the canonical uses of objects they stop interacting with isolated things and start to interact with members of functional classes. Knowledge about the canonical function of objects grants children access to new forms of interaction with the material world, with others, and with themselves. I, therefore, propose that, in early childhood, general forms of material engagement that take place within culturally organised activities are central to conceptual development. Specifically, I hold that canonical uses of objects are conceptual in nature. Results are discussed in relation to the need for more studies addressing the active role of material culture for cognition in early childhood. (shrink)

We present a systematic and qualitative review of academic literature on early conceptual development (0–24 months of age), with an emphasis on methodological aspects. The final sample of our review included 281 studies reported in 115 articles. The main aims of the article were four: first, to organise studies into sets according to methodological similarities and differences; second, to elaborate on the methodological procedures that characterise each set; third, to circumscribe the empirical indicators that different sets of studies consider as (...) proof of the existence of concepts in early childhood; last, to identify methodological limitations and to propose possible ways to overcome them. We grouped the studies into five sets: preference and habituation experiments, category extension tasks, object sorting tasks, sequential touching tasks and object examination tasks. In the “Results” section, we review the core features of each set of studies. In the “Discussion” and “Conclusions” sections, we describe, for one thing, the most relevant methodological shortcomings. We end by arguing that a situated, semiotic and pragmatic perspective that emphasises the importance of ecological validity could open up new avenues of research to better understand the development of concepts in early childhood. (shrink)

The purpose of this paper is to provide a detailed technical protocol analysis of chess masters' evaluative expertise, paying particular attention to the analysis of the structure of their memory process in evaluating foreseen possibilities in games of dynamic equilibrium. The paper has two purposes. First, to publish a results chapter from my DPhil thesis (in revised journal article form) attending to the measurement of foresight in chess masters' evaluation process, testing alternative theories of cognitive expertise in the domain of (...) chess; and second to provide a subset of the technical graphical analysis that corresponds to that measurement to preserve this protocol analysis for access in the academic domain for future studies of expert memory and foresight (e.g., Ericsson & Simon, 1993). The step-by-step protocol analysis consists of: (i) an introduction to foresight cognition as hypothesis testing, (ii) a theoretical review in the domain of chess masters' expertise according to the theoretical frameworks in that field purporting hypotheses relevant to chess masters' evaluative skill processes, and (iii) summary tables and non-parametric statistical analysis corroborating chunking theory frameworks of expert cognition (e.g., DeGroot, 1965; Newell & Simon, 1972; Gobet, 1998; Gobet et al., 2004), and refuting the alternative search-evaluation models (e.g., Holding & Reynolds, 1982). Moreover, the journal article espouses the preservation of the traditional protocol analysis method core to the field of expert cognition (DeGroot, 1969; Kotov, 1971). The full protocol analysis can be found in monograph form here on my SSRN profile in ‘The role of falsification in hypothesis testing’. It takes the form of a specialist population study (e.g., detailed case study work; Luria, 1987). Thus the outline consists of a short introduction, a theoretical methodological review discussing protocol analysis methods for specialist population studies in cognition (with particular attention to the preservation of protocol analysis methods for chess studies in cognition and expert memory/ with a fresh angle on the foresight process), and the full set of protocol analyses with corresponding problem behaviour graphs. A subset of the main results has been published elsewhere (e.g., Cowley & Byrne, 2004; Cowley 2006), receiving scientific and scientific journalistic acclaim (e.g., Nature Online News 2004). (shrink)

Two main cognitive theories predict that people find refuting evidence that falsifies their theorising difficult, if not impossible to consider, even though such reasoning may be pivotal to grounding their everyday thoughts in reality (i.e., Poletiek, 1996; Klayman & Ha, 1987). In the classic 2-4-6 number sequence task devised by psychologists to test such reasoning skills in a simulated environment – people fail the test more often than not. In the 2-4-6 task participants try to discover what rule the number (...) triple 2-4-6 conforms to. The rule is ‘ascending numbers’, but it is tricky to discover this rule. Participants tend to generate hypotheses with the properties of the 2-4-6 triple, for example, ‘even numbers ascending in twos’. They must search for evidence to test whether their hypothesis is the rule. But experimental evidence has shown that they tend to generate confirming triples that they expect to be consistent with their hypothesis rather than inconsistent falsifying triples. Counter to the two main hypothesis testing theories this paper demonstrates that falsification is possible in five 2-4-6 task experiments when participants consider an Imaginary Participant’s hypothesis. Experiment 1 and 2 show that competition with an opponent hypothesis tester facilitates falsification. Experiments 3 to 5 show that the consideration of an alternative hypothesis helps this falsification of hypotheses lead to rule discovery. The implications of the results for theories of hypothesis testing and reasoning are discussed. (shrink)

Each day people are presented with circumstances that may require speculation. Scientists may ponder questions such as why a star is born or how rainbows are made, psychologists may ask social questions such as why people are prejudiced, and military strategists may imagine what the consequences of their actions might be. Speculations may lead to the generation of putative explanations called hypotheses. But it is by checking if hypotheses accurately reflect the encountered facts that lead to sensible behaviour demonstrating a (...) true understanding. If evidence shows a hypothesis to be false, then people should rationally abandon it, especially if there are negative consequences. The aim of this thesis is to examine how effectively people search for evidence in their hypothesis testing to test whether or not their hypotheses are true or false in competitive games. -/- Research findings from six studies of hypothesis testing behaviour in competitive deductive tasks are explored. Chapter by chapter the thesis tests how everyday people, and master chess players, tackle hypothesis testing in mathematical tasks, such as how to solve sequential number sequence puzzles when thinking about an opponent, or how to solve chess problems in a variety of contexts. The implications of the results are discussed in light of aspects of general cognition: such as reasoning, social hypothesis testing and planning. (shrink)

A problem is a difference between what a person has and wants. A solution is anything that reduces the difference. These two simple definitions form the foundation of an ecological perspective on the often-complex, reciprocal relationships among people, their environments and their behaviours—a perspective that mixes causal ideas from psychology with consequential ideas from economics. The present article offers a brief introduction to this perspective and suggests how it might be instantiated by naturalistic observations and content analyses of narratives.

The book is addressed to all readers interested in cognitive science, and especially in research combining a logical analysis with psychological, linguistic and neurobiological approaches. The publication is the result of a collaboration between the Department of Cognitive Science at University of Lodz and the Department of Cognitive Science at Lund University. It is intended to provide a comprehensive presentation of the key research issues undertaken in both Departments, including considerations on meaning, natural language and reasoning, linguistic as well as (...) numerical competence, the theory of decision making, modelling of conceptual representations, cognitive and game theoretic approach to social interactions. (shrink)

We overview logical and computational explanations of the notion of tractability as applied in cognitive science. We start by introducing the basics of mathematical theories of complexity: computability theory, computational complexity theory, and descriptive complexity theory. Computational philosophy of mind often identifies mental algorithms with computable functions. However, with the development of programming practice it has become apparent that for some computable problems finding effective algorithms is hardly possible. Some problems need too much computational resource, e.g., time or memory, to (...) be practically computable. Computational complexity theory is concerned with the amount of resources required for the execution of algorithms and, hence, the inherent difficulty of computational problems. An important goal of computational complexity theory is to categorize computational problems via complexity classes, and in particular, to identify efficiently solvable problems and draw a line between tractability and intractability. -/- We survey how complexity can be used to study computational plausibility of cognitive theories. We especially emphasize methodological and mathematical assumptions behind applying complexity theory in cognitive science. We pay special attention to the examples of applying logical and computational complexity toolbox in different domains of cognitive science. We focus mostly on theoretical and experimental research in psycholinguistics and social cognition. (shrink)

Experiments are presented showing that visual search for Mueller-Lyer (ML) stimuli is based on complete configurations, rather than component segments. Segments easily detected in isolation were difficult to detect when embedded in a configuration, indicating preemption by low-level groups. This preemption—which caused stimulus components to become inaccessible to rapid search—was an all-or-nothing effect, and so could serve as a powerful test of grouping. It is shown that these effects are unlikely to be due to blurring by simple spatial filters at (...) early visual levels. It is proposed instead that they are due to more sophisticated processes that rapidly bind contour fragments into spatially-extended assemblies. These results support the view that rapid visual search cannot access the primitives formed at the earliest stages of visual processing; rather, it can access only higher-level, more ecologically-relevant structures. (shrink)

The book from which these sections are excerpted is concerned with the prospects for assimilating the study of human intelligence and its products to the natural sciences through the investigation of cognitive structures, understood as systems of rules and representations that can be regarded as “mental organs.” These mental structui′es serve as the vehicles for the exercise of various capacities. They develop in the mind on the basis of an innate endowment that permits the growth of rich and highly articulated (...) structures along an intrinsically determined course under the triggering and partially shaping effect of experience, which fixes parameters in an intricate system of predetermined form. It is argued that the mind is modular in character, with a diversity of cognitive structures, each with its specific properties arid principles. Knowledge of language, of the behavior of objects, and much else crucially involves these mental structures, and is thus not characterizable in terms of capacities, dispositions, or practical abilities, nor is it necessarily grounded in experience in the standard sense of this term.Various types of knowledge and modes of knowledge acquisition are discussed in these terms. Some of the properties of the language faculty are investigated. The basic cognitive relation is “knowing a grammar”; knowledge of language is derivative and, correspondingly, raises further problems. Language as commonly understood is not a unitary phenomenon but involves a number of interacting systems: the “computational” system of grammar, which provides the representations of sound and meaning that permit a rich range of expressive potential, is distinct from a conceptual system with its own properties; knowledge of language must be distinguished from knowledge of how to use a language; and the various systems that enter into the knowledge and use of language must be further analyzed into their specific subcomponents. (shrink)

Concept Pluralism and Concept Eliminativism are two positions recently proposed in the philosophy and the psychology of concepts. Both of these theories are motivated by the view that all current theories of concepts are empirically and methodologically inadequate and hold in common the assumption that for any category that can be represented in thought, a person can possess multiple, distinct concepts of it. In this paper, I will challenge these in light of a third theory, Conceptual Atomism, which addresses and (...) dispels the contentious issues. In particular, I contend that Conceptual Atomism, when properly understood, is empirically adequate and can overcome difficulties that plague Pluralism and Eliminativism. (shrink)

The article identifies some key findings in pedagogical research over recent decades, placing them within a framework of logical curriculum development and current practice in quality assurance and enhancement. Throughout, the ideas and comments are related to the practice of teaching classics in university.

Many of the problems studied in cognitive science are inductive problems, requiring people to evaluate hypotheses in the light of data. The key to solving these problems successfully is having the right inductive biases—assumptions about the world that make it possible to choose between hypotheses that are equally consistent with the observed data. This article explores a novel experimental method for identifying the biases that guide human inductive inferences. The idea behind this method is simple: This article uses the responses (...) produced by a participant on one trial to generate the stimuli that either they or another participant will see on the next. A formal analysis of this “iterated learning” procedure, based on the assumption that the learners are Bayesian agents, predicts that it should reveal the inductive biases of these learners, as expressed in a prior probability distribution over hypotheses. This article presents a series of experiments using stimuli based on a well-studied set of category structures, demonstrating that iterated learning can be used to reveal the inductive biases of human learners. (shrink)

This paper addresses the question whether we can conceive of music cognition in ecosemiotic terms. It claims that music knowledge must be generated as a tool for adaptation to the sonic world and calls forth a shift from a structural description of music as an artifact to a process-like approach to dealing with music. As listeners, we are observers who construct and organize our knowledge and bring with us our observational tools. What matters is not merely the sonic world in (...) its objective qualities, but the world as perceived. In order to make these claims operational we can rely on the ecological concept of coping with the sonic world and the cybernetic concepts of artificial and adaptive devices. Listeners, on this view, are able to change their semantic relations with the sonic world through functional adaptations at the level of sensing, acting and coordinating between action and perception. This allows us to understand music in functional terms of what it affords to us and not merely in terms of its acoustic qualities. There are, however, degrees of freedom and constraints which shape the semiotization of the sonic world. As such we must consider the role of event perception and cognitive economy: listeners do not perceive the acoustical environment in terms of phenomenological descriptions but as ecological events. (shrink)

Normal children learn tens of thousands of words, and do so quickly and efficiently, often in highly impoverished environments. In How Children Learn the Meanings of Words, I argue that word learning is the product of certain cognitive and linguistic abilities that include the ability to acquire concepts, an appreciation of syntactic cues to meaning, and a rich understanding of the mental states of other people. These capacities are powerful, early emerging, and to some extent uniquely human, but they are (...) not special to word learning. This proposal is an alternative to the view that word learning is the result of simple associative learning mechanisms, and it rejects as well the notion that children possess constraints, either innate or learned, that are specifically earmarked for word learning. This theory is extended to account for how children learn names for objects, substances, and abstract entities, pronouns and proper names, verbs, determiners, prepositions, and number words. Several related topics are also discussed, including naïve essentialism, children's understanding of representational art, the nature of numerical and spatial reasoning, and the role of words in the shaping of mental life. Key Words: cognitive development; concepts; meaning; semantics; social cognition; syntax; theory of mind; word learning. (shrink)

This paper addresses the question whether we can conceive of music cognition in ecosemiotic terms. It claims that music knowledge must be generated as a tool for adaptation to the sonic world and calls forth a shift from a structural description of music as an artifact to a process-like approach to dealing with music. As listeners, we are observers who construct and organize our knowledge and bring with us our observational tools. What matters is not merely the sonic world in (...) its objective qualities, but the world as perceived. In order to make these claims operational we can rely on the ecological concept of coping with the sonic world and the cybernetic concepts of artificial and adaptive devices. Listeners, on this view, are able to change their semantic relations with the sonic world through functional adaptations at the level of sensing, acting and coordinating between action and perception. This allows us to understand music in functional terms of what it affords to us and not merely in terms of its acoustic qualities. There are, however, degrees of freedom and constraints which shape the semiotization of the sonic world. As such we must consider the role of event perception and cognitive economy: listeners do not perceive the acoustical environment in terms of phenomenological descriptions but as ecological events. (shrink)

The book from which these sections are excerpted is concerned with the prospects for assimilating the study of human intelligence and its products to the natural sciences through the investigation of cognitive structures, understood as systems of rules and representations that can be regarded as These mental structui′es serve as the vehicles for the exercise of various capacities. They develop in the mind on the basis of an innate endowment that permits the growth of rich and highly articulated structures along (...) an intrinsically determined course under the triggering and partially shaping effect of experience, which fixes parameters in an intricate system of predetermined form. It is argued that the mind is modular in character, with a diversity of cognitive structures, each with its specific properties arid principles. Knowledge of language, of the behavior of objects, and much else crucially involves these mental structures, and is thus not characterizable in terms of capacities, dispositions, or practical abilities, nor is it necessarily grounded in experience in the standard sense of this term. (shrink)

The use of list-learning paradigms to explore false memory has revealed several critical findings about the contributions of similarity and relatedness in memory phenomena more broadly. Characterizing the nature of “similarity and relatedness” can inform researchers about factors contributing to memory distortions and about the underlying associative and semantic networks that support veridical memory. Similarity can be defined in terms of semantic properties (e.g., shared conceptual and taxonomic features), lexical/associative properties (e.g., shared connections in associative networks), or structural properties (e.g., (...) shared orthographic or phonological features). By manipulating the type of list and its relationship to a non-studied critical item, we review the effects of these types of similarity on veridical and false memory. All forms of similarity reviewed here result in reliable error rates and the effects on veridical memory are variable. The results across a variety of paradigms and tests provide partial support for a number of theoretical explanations of false memory phenomena, but none of the theories readily account for all results. (shrink)

Dispositionalism about belief has had a recent resurgence. In this paper we critically evaluate a popular dispositionalist program pursued by Eric Schwitzgebel. Then we present an alternative: a psychofunctional, representational theory of belief. This theory of belief has two main pillars: that beliefs are relations to structured mental representations, and that the relations are determined by the generalizations under which beliefs are acquired, stored, and changed. We end by describing some of the generalizations regarding belief acquisition, storage, and change.

Most cognitive psychology experiments evaluate models of human cognition using a relatively small, well-controlled set of stimuli. This approach stands in contrast to current work in neuroscience, perception, and computer vision, which have begun to focus on using large databases of natural images. We argue that natural images provide a powerful tool for characterizing the statistical environment in which people operate, for better evaluating psychological theories, and for bringing the insights of cognitive science closer to real applications. We discuss how (...) some of the challenges of using natural images as stimuli in experiments can be addressed through increased sample sizes, using representations from computer vision, and developing new experimental methods. Finally, we illustrate these points by summarizing recent work using large image databases to explore questions about human cognition in four different domains: modeling subjective randomness, defining a quantitative measure of representativeness, identifying prior knowledge used in word learning, and determining the structure of natural categories. (shrink)

The paper begins by drawing a number of ‘levels’ distinctions in epistemology. It notes that a theory of knowledge must be an attempt to obtain knowledge . It is suggested that we can make sense of much of the work found in analytic theory of knowledge by seeing three framework assumptions as underpinning this work. First, that to have philosophical knowledge of knowledge requires us to have an analysis. Second, that much of what we require from a theory of knowledge (...) may be obtained by developing such analyses of first-order, concrete, empirical, propositional knowledge. Third, that the final arbiter of the correctness of such analyses is to be the carefully examined intuitions of the epistemologist. The paper attacks each aspect of this framework on the ground that this methodology will precisely not give us knowledge . In passing, comparisons are drawn with arguments that led to the demise of phenomenalism. The paper concludes with remarks about realism/anti-realism and consensus/disagreement in analytic epistemology. The paper recommends that we seek to develop theories of knowledge rather than analyses, and defends the position that such theories will precisely not be analyses. (shrink)

The purpose of the two studies reported here was to develop an integrated model of the scientific reasoning process. Subjects were placed in a simulated scientific discovery context by first teaching them how to use an electronic device and then asking them to discover how a hitherto unencountered function worked. To do this task, subjects had to formulate hypotheses based on their prior knowledge, conduct experiments, and evaluate the results of their experiments. In the first study, using 20 adult subjects, (...) we identified two main strategies that subjects used to generate new hypotheses. One strategy was to search memory and the other was to generalize from the results of previous experiments. We described the former group as searching an hypothesis space, and the latter as searching an experiment space. In a second study, with 10 adults, we investigated how subjects search the hypothesis space by instructing them to state all the hypotheses that they could think of prior to conducting any experiments. Following this phase, subjects were then allowed to conduct experiments. Subjects who could not think of the correct rule in the hypothesis generation phase discovered the correct rule only by generalizing from the results of experiments in the experimental phase.Both studies provide support for the view that scientific reasoning can be characterized as search in two problem spaces. By extending Simon and Lea's (1974) Generalized Rule Inducer, we present a general model of Scientific Discovery as Dual Search (SDDS) that shows how search in two problem spaces (an hypothesis space and an experiment space) shapes hypothesis generation, experimental design, and the evaluation of hypotheses. The model also shows how these processes interact with each other. Finally, we interpret earlier findings about the psychology of scientific reasoning in terms of the SDDS model. (shrink)

Information about the structure of a causal system can come in the form of observational data—random samples of the system's autonomous behavior—or interventional data—samples conditioned on the particular values of one or more variables that have been experimentally manipulated. Here we study people's ability to infer causal structure from both observation and intervention, and to choose informative interventions on the basis of observational data. In three causal inference tasks, participants were to some degree capable of distinguishing between competing causal hypotheses (...) on the basis of purely observational data. Performance improved substantially when participants were allowed to observe the effects of interventions that they performed on the systems. We develop computational models of how people infer causal structure from data and how they plan intervention experiments, based on the representational framework of causal graphical models and the inferential principles of optimal Bayesian decision‐making and maximizing expected information gain. These analyses suggest that people can make rational causal inferences, subject to psychologically reasonable representational assumptions and computationally reasonable processing constraints. (shrink)

This paper explores a new reason for preferring a model-theoretic approach to understanding the nature of scientific theories. Identifying the models in philosophers' model-theoretic accounts of theories with the concepts in cognitive scientists' accounts of categorization suggests a structure to families of models far richer than has commonly been assumed. Using classical mechanics as an example, it is argued that families of models may be "mapped" as an array with "horizontal" graded structures, multiply hierarchical "vertical" structures, and local "radial" structures. (...) These structures promise important implications for how scientific theories are learned and used in actual scientific practice. (shrink)

Algorithms for approximate Bayesian inference, such as those based on sampling (i.e., Monte Carlo methods), provide a natural source of models of how people may deal with uncertainty with limited cognitive resources. Here, we consider the idea that individual differences in working memory capacity (WMC) may be usefully modeled in terms of the number of samples, or “particles,” available to perform inference. To test this idea, we focus on two recent experiments that report positive associations between WMC and two distinct (...) aspects of categorization performance: the ability to learn novel categories, and the ability to switch between different categorization strategies (“knowledge restructuring”). In favor of the idea of modeling WMC as a number of particles, we show that a single model can reproduce both experimental results by varying the number of particles—increasing the number of particles leads to both faster category learning and improved strategy‐switching. Furthermore, when we fit the model to individual participants, we found a positive association between WMC and best‐fit number of particles for strategy switching. However, no association between WMC and best‐fit number of particles was found for category learning. These results are discussed in the context of the general challenge of disentangling the contributions of different potential sources of behavioral variability. (shrink)

One of the most discussed issues in psychology—presently and in the past—is how to define and measure the extent to which human cognition is rational. The rationality of human cognition is often evaluated in terms of normative standards based on a priori intuitions. Yet this approach has been challenged by two recent developments in psychology that we review in this article: ecological rationality and descriptivism. Going beyond these contributions, we consider it a good moment for psychologists and philosophers to join (...) forces and work toward a new foundation for the definition of rational cognition. We take a first step in this direction by proposing that the rationality of both cognitive and normative systems can be measured in terms of their cognitive success. Cognitive success can be defined and gauged in terms of two factors: ecological validity (the system's validity in conditions in which it is applicable) and the system's applicability (the scope of conditions under which it can be applied). As we show, prominent systems of reasoning—deductive reasoning, Bayesian reasoning, uncertain conditionals, and prediction and choice—perform rather differently on these two factors. Furthermore, we demonstrate that conceptualizing rationality according to its cognitive success offers a new perspective on the time-honored relationship between the descriptive (“is”) and the normative (“ought”) in psychology and philosophy. (shrink)

Six experiments investigated variables predicted to influence subjects’ tendency to classify items by a single property instead of overall similarity, following the paradigm of Norenzayan et al., who found that European Americans tended to give more “logical” rule-based responses. However, in five experiments with Mechanical Turk subjects and undergraduates at an American university, we found a consistent preference for similarity-based responding. A sixth experiment with Korean undergraduates revealed an effect of instructions, also reported by Norenzayan et al., in which classification (...) instructions led to majority rule-based responding but similarity instructions led to overall similarity grouping. Our American subjects showed no such difference and used similarity more overall. We conclude that Americans do not have a preference for rule responding in classification and discuss the differences between tasks that reliably show strong rule or unidimensional preferences in contrast to this classification paradigm. (shrink)