The goal of this research is to understand the interaction of implicit and explicit psychological processes in dealing with emotional distractions and meta-cognitive control of such distractions. The questions are how emotional and meta-cognitive processes can be separated into implicit and explicit components, and how such a separation can be utilized to improve self-regulation of emotion, which can have significant theoretical and practical implications.

In a series of publications, Tamar Gendler has argued for a distinction between belief and what she calls ?alief?. Gendler's argument for the distinction is a serviceability argument: the distinction is indispensable for explaining a whole slew of phenomena, typically involving ?belief-behaviour mismatch?. After embedding Gendler's distinction in a dual-process model of moral cognition, I argue here that the distinction also suggests a possible (dis)solution of what is perhaps the organizing problem of contemporary moral psychology: the apparent tension between the (...) inherently motivational role of moral judgments and their manifestly objectivistic phenomenology. I argue that moral judgments come in two varieties, moral aliefs and moral beliefs, and it is only the former that are inherently motivating and only the latter that have an objectivistic phenomenology. This serves to both bolster the case for the alief/belief distinction and shed new light on otherwise well-trodden territory in metaethics. I start with an exposition of the moral-psychological problem (?1) and a discussion of Gendler's alief/belief distinction (?2). I then apply the latter to moral judgments in an attempt to dissolve the former (?3). I close with discussion of the upshot for our understanding of moral thought, moral motivation, and moral phenomenology (?4). (shrink)

This paper describes how meta-cognitive processes (i.e., the self monitoring and regulating of cognitive processes) may be captured within a cognitive architecture Clarion. Some currently popular cognitive architectures lack sufficiently complex built-in meta-cognitive mechanisms. However, a sufficiently complex meta-cognitive mechanism is important, in that it is an essential part of cognition and without it, human cognition may not function properly. We contend that such a meta-cognitive mechanism should be an integral part of a cognitive architecture. Thus such a mechanism has (...) been developed within the Clarion cognitive architecture. The paper demonstrates how human data of two meta-cognitive experiments are simulated using Clarion. The simulations show that the meta-cognitive processes represented by the experimental data (and beyond) can be adequately captured within the Clarion framework. (shrink)

The phenomenon of base-rate neglect has elicited much debate. One arena of debate concerns how people make judgments under conditions of uncertainty. Another more controversial arena concerns human rationality. In this target article, we attempt to unpack the perspectives in the literature on both kinds of issues and evaluate their ability to explain existing data and their conceptual coherence. From this evaluation we conclude that the best account of the data should be framed in terms of a dual-process model of (...) judgment, which attributes base-rate neglect to associative judgment strategies that fail to adequately represent the set structure of the problem. Base-rate neglect is reduced when problems are presented in a format that affords accurate representation in terms of nested sets of individuals. (shrink)

In this paper I criticize the most significant recent examples of the practical knowledge analysis of knowledge-how in the philosophical literature: David Carr [1979, Mind, 88, 394–409; 1981a, American Philosophical Quarterly, 18, 53–61; 1981b, Journal of Philosophy of Education, 15(1), 87–96] and Stanley & Williamson [2001, Journal of Philosophy, 98(8), 411–444]. I stress the importance of know-how in our contemporary understanding of the mind, and offer the beginnings of a treatment of know-how capable of providing insight in to the use (...) of know-how in contemporary cognitive science. Specifically, I claim that Carr’s necessary conditions for know-how fail to capture the distinction he himself draws between ability and knowing-how. Moreover, Carr ties knowing-how to conscious intent, and to an explicit knowledge of procedural rules. I argue that both moves are mistakes, which together render Carr’s theory an inadequate account both of common ascriptions of knowledge-how and of widely accepted ascriptions of knowledge-how within explanations in cognitive science. Finally, I note that Carr’s conditions fail to capture intuitions (heshares) regarding the ascription of know-how to persons lacking ability. I then consider the position advocated by Stanley & Williamson (2001), which seems avoid Carr’s commitments to conscious intent and explicit knowledge while still maintaining that “knowledge-how is simply a species of knowledge-that" (Stanley & Williamson, 2001, p. 411). I argue that Stanley and Williamson’s attempt to frame a reductionist view that avoids consciously occurrent beliefs during exercises of knowledge-how and explicit knowledge of procedural rules is both empirically implausible and explanatorily vacuous. In criticizing these theories I challenge the presuppositions of the most pervasive response to Ryle in the philosophic literature, what might be described as “the received view." I also establish several facts about knowing-how. First, neither conscious intent nor explicit representation (much less conscious representation) of procedural rules are necessary for knowing-how given the theory of cognition current in cognitive science. I argue that the discussed analyses fail to capture the necessary conditions for knowledge-how because know-how requires the instantiation of an ability and of the capacities necessary for exploiting an ability—not conscious awareness of purpose or explicit knowledge of rules. Second, one must understand knowledge-how as task-specific, i.e., as presupposing certain underlying conditions. Conceiving of know-how as task-specific allows one to understand ascriptions of know-how in the absence of ability as counterfactual ascriptions based upon underlying competence. (shrink)

Although statistical learning (SL) has been studied extensively in developmental dyslexia (DD), less attention has been paid to other fundamental challenges in language acquisition, such as cross-situational word learning. Such investigation is important for determining whether and how SL processes are affected in DD at the word level. In this study, typically developed (TD) adults and young adults with DD were exposed to a set of trials that contained multiple spoken words and multiple pictures of individual objects, with no information (...) about word-referent correspondences provided within a trial. Nonetheless, cross-trial statistical relations could be exploited to learn word-referent mappings. The degree of within-trial reference uncertainty and the novelty of to-be-learned objects (novel or familiar) were varied under different learning conditions. The results show that across all conditions, young adults with DD were significantly impaired in their ability to exploit cross-trial regularities in co-occurring visual–auditory streams to discover word-referent mappings. Observed impairments were most pronounced when within-trial reference uncertainty was the highest. Subjective measures of knowledge awareness revealed greater development of implicit but not explicit knowledge in the TD group than in the DD group. Together, these findings suggest that the SL deficit in DD affects fundamental language learning challenges at the word level and points to greater reliance on explicit processes due to impaired implicit associative learning among individuals with DD. Such a deficit is likely to influence spoken language acquisition, and in turn affect literacy skills, in people with DD. (shrink)

Although many studies have provided evidence that abstract knowledge can be acquired in artificial grammar learning, it remains unclear how abstract knowledge can be attained in sequence learning. To address this issue, we proposed a dual simple recurrent network model that includes a surface SRN encoding and predicting the surface properties of stimuli and an abstract SRN encoding and predicting the abstract properties of stimuli. The results of Simulations 1 and 2 showed that the DSRN model can account for learning (...) effects in the serial reaction time task under different conditions, and the manipulation of the contribution weight of each SRN accounted for the contribution of conscious and unconscious processes in inclusion and exclusion tests in previous studies. The results of human performance in Simulation 3 provided further evidence that people can implicitly learn both chunking and abstract knowledge in sequence learning, and the results of Simulation 3 confirmed that the DSRN model can account for how people implicitly acquire the two types of knowledge in sequence learning. These findings extend the learning ability of the SRN model and help understand how different types of knowledge can be acquired implicitly in sequence learning. (shrink)

According to cognitive psychologists, moral decision-making is a dual-process phenomenon involving two types of cognitive processes: explicit reasoning and implicit intuition. Moral development involves training and integrating both types of cognitive processes through a mix of instruction, practice, and reflection. Serious games are an ideal platform for this kind of moral training, as they provide safe spaces for exploring difficult moral problems and practicing the skills necessary to resolve them. In this article, we present Morality Play, a model for the (...) design of serious games for ethical expertise development based on the Integrative Ethical Education framework from moral psychology and the Lens of the Toy model for serious game design. (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)

Concurrent adaptation to two different visuomotor transformations has been shown to be possible as long as discriminative contextual cues are available. The authors examined explicit and implicit components of visually cued dual adaptation in younger and older adults. They found that only young adults, but not old adults, produced appropriate adaptive shifts of hand-movement direction to compensate for the visuomotor rotations. Aftereffects, conceived as a measure of implicit knowledge, were only poorly developed. Furthermore, only participants in the younger group exhibited (...) systematic explicit knowledge of the visuomotor rotations. Subsequent analyses revealed strong correlations between the quality of explicit knowledge and the overall visuomotor adaptation. Thus, visually cued dual adaptation to two opposite visuomotor rotations is primarily mediated by conscious strategic corrections based on explicit knowledge of the transformations, a process, which is selectively impaired in older adults. (shrink)

ABSTRACTThis article focuses on the relationship between cultural and cognitive-psychological processes, and discusses the potential impact of the cognitive sciences on understand...

Previous studies of auditory expectation have focused on the expectedness perceived by listeners retrospectively in response to events. In contrast, this research examines predictive uncertainty —a property of listeners' prospective state of expectation prior to the onset of an event. We examine the information-theoretic concept of Shannon entropy as a model of predictive uncertainty in music cognition. This is motivated by the Statistical Learning Hypothesis, which proposes that schematic expectations reflect probabilistic relationships between sensory events learned implicitly through exposure. Using (...) probability estimates from an unsupervised, variable-order Markov model, 12 melodic contexts high in entropy and 12 melodic contexts low in entropy were selected from two musical repertoires differing in structural complexity (simple and complex). Musicians and non-musicians listened to the stimuli and provided explicit judgments of perceived uncertainty (explicit uncertainty). We also examined an indirect measure of uncertainty computed as the entropy of expectedness distributions obtained using a classical probe-tone paradigm where listeners rated the perceived expectedness of the final note in a melodic sequence (inferred uncertainty). Finally, we simulate listeners' perception of expectedness and uncertainty using computational models of auditory expectation. A detailed model comparison indicates which model parameters maximize fit to the data and how they compare to existing models in the literature. The results show that listeners experience greater uncertainty in high-entropy musical contexts than low-entropy contexts. This effect is particularly apparent for inferred uncertainty and is stronger in musicians than non-musicians. Consistent with the Statistical Learning Hypothesis, the results suggest that increased domain-relevant training is associated with an increasingly accurate cognitive model of probabilistic structure in music. (shrink)

This paper discusses essential motivational representations necessary for a comprehensive computational cognitive architecture. It hypothesizes the need for implicit drive representations, as well as explicit goal representations. Drive representations consist of primary drives — both low-level primary drives (concerned mostly with basic physiological needs) and high-level primary drives (concerned more with social needs), as well as derived (secondary) drives. On the basis of drives, explicit goals may be generated on the fly during an agent’s interaction with various situations. These motivational (...) representations help to make cognitive architectural models more comprehensive and provide deeper explanations of psychological processes. This work represents a step forward in making computational cognitive architectures better reflections of the human mind and all its motivational complexity and intricacy. (shrink)

Most psychological theories of problem solving have focused on modeling explicit processes that gradually bring the solver closer to the solution in a mostly explicit and deliberative way. This approach to problem solving is typically inefficient when the problem is too complex, ill-understood, or ambiguous. In such a case, a ‘creative’ approach to problem solving might be more appropriate. In the present paper, we propose a computational psychological model implementing the Explicit-Implicit Interaction theory of creative problem solving that involves integrating (...) the results of implicit and explicit processing. In this paper, the new model is used to simulate insight in creative problem solving and the overshadowing effect. (shrink)

We agree that current evolutionary accounts of base-rate neglect are unparsimonious, but we dispute the authors' account of the effect in terms of parallel associative and rule-based processes. We also question their assumption that cueing of nested set relations facilitates performance due to recruitment of explicit reasoning processes. In our account, such reasoning is always involved, but usually unsuccessful.

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)

People are unable to report how they decide whether to move backwards or forwards to catch a ball. When asked to imagine how their angle of elevation of gaze would change when they caught a ball, most people are unable to describe what happens although their interception strategy is based on controlling changes in this angle. Just after catching a ball, many people are unable to recognise a description of how their angle of gaze changed during the catch. Some people (...) confidently choose incorrect descriptions that would guarantee failure of interception demonstrating unconscious knowledge co-existing with systematically different conscious beliefs. Where simple solutions to important evolutionary problems exist, unconscious perception needs to be impervious to conscious beliefs. (shrink)

Research in computational cognitive modeling investigates the nature of cognition through developing process-based understanding by specifying computational models of mechanisms (including representations) and processes. In this enterprise, a cognitive architecture is a domaingeneric computational cognitive model that may be used for a broad, multiple-level, multipledomain analysis of behavior. It embodies generic descriptions of cognition in computer algorithms and programs. Developing cognitive architectures is a difficult but important task. In this article, discussions of issues and challenges in developing cognitive architectures will (...) be undertaken, and an example cognitive architecture (CLARION) will be described. (shrink)

Explicit and implicit learning have been attributed to different learning processes that create different types of knowledge structures. Consistent with that claim, our study provides evidence that people integrate stimulus events differently when consciously aware versus unaware of the relationship between the events. In a first, acquisition phase participants sorted words into two categories , which were fully predicted by task-irrelevant primes—the labels of two other, semantically unrelated categories . In a second, test phase participants performed a lexical decision task, (...) in which all word stimuli stemmed from the previous prime categories and the primes were the labels of the previous target categories . Reliable priming effects in the second phase demonstrated that bidirectional associations between the respective categories had been formed in the acquisition phase , but these effects were found only in participants that were unaware of the relationship between the categories! We suggest that unconscious, implicit learning of event relationships results in the rather unsophisticated integration of the underlying event representations, whereas explicit learning takes the meaning of the order of the events into account, and thus creates unidirectional associations. (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)

We report the results of an experiment in which human subjects were trained to perform a perceptual matching task. Subjects were asked to manipulate comparison objects until they matched target objects using the fewest manipulations possible. An unusual feature of the experimental task is that efficient performance requires an understanding of the hidden or latent causal structure governing the relationships between actions and perceptual outcomes. We use two benchmarks to evaluate the quality of subjects’ learning. One benchmark is based on (...) optimal performance as calculated by a dynamic programming procedure. The other is based on an adaptive computational agent that uses a reinforcement-learning method known as Q-learning to learn to perform the task. Our analyses suggest that subjects were successful learners. In particular, they learned to perform the perceptual matching task in a near-optimal manner (i.e., using a small number of manipulations) at the end of training. Subjects were able to achieve near-optimal performance because they learned, at least partially, the causal structure underlying the task. In addition, subjects’ performances were broadly consistent with those of model-based reinforcement-learning agents that built and used internal models of how their actions influenced the external environment. We hypothesize that people will achieve near-optimal performances on tasks requiring sequences of action—especially sensorimotor tasks with underlying latent causal structures—when they can detect the effects of their actions on the environment, and when they can represent and reason about these effects using an internal mental model. (shrink)

Although computational models of cognitive agents that incorporate a wide range of cognitive functionalities have been developed in cognitive science, most of the work in social simulation still assumes rudimentary cognition on the part of the agents. In contrast, in this work, the interaction of cognition and social structures/processes is explored, through simulating survival strategies of tribal societies. The results of the simulation demonstrate interactions between cognitive and social factors. For example, we show that cognitive capabilities and tendencies may be (...) relevant to what social institutions may be adopted. This work points to a cognitively based approach towards social simulation, as well as a new area of research—exploring the cognitive–social interaction through cognitively based social simulation. (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)

This article explores the view that computational models of cognition may constitute valid theories of cognition, often in the full sense of the term ‘‘theory”. In this discussion, this article examines various (existent or possible) positions on this issue and argues in favor of the view above. It also connects this issue with a number of other relevant issues, such as the general relationship between theory and data, the validation of models, and the practical benefits of computational modeling. All the (...) discussions point to the position that computational cognitive models can be true theories of cognition. Ó 2008 Elsevier B.V. All rights reserved. (shrink)

In a highly influential work, List and Pettit (Group Agency: The Possibility, Design, and Status of Corporate Agents, Oxford University Press, 2011) draw upon the theory of judgement aggregation to offer an argument for the existence of nonreductive group agents; they also suggest that nonreductive group agency is a widespread phenomenon. In this paper, we argue for the following two claims. First, that the axioms they consider cannot naturally be interpreted as either descriptive characterisations or normative constraints upon group judgements, (...) in general. This makes it unclear how the List and Pettit argument is to apply to real world group behaviour. Second, by examining empirical data about how group judgements are made by a powerful international regulatory board, we show how each of the List and Pettit axioms can be violated in ways which are straightforwardly explicable at the level of the individual. This suggests that group agency may best be understood as a pluralistic phenomenon, where close inspection of the dynamics of intragroup deliberation can reveal that what prima facie appears to be a nonreductive group agent is, in fact, reducible. (shrink)

Sciences able to identify appropriate analytical units for their domain, their natural kinds, have tended to be more progressive. In the biological sciences, evolutionary natural kinds are adaptations that can be identified by their common history of selection for some function. Human brains are the product of an evolutionary history of selection for component systems which produced behaviours that gave adaptive advantage to their hosts. These structures, behaviour production systems, are the natural kinds that psychology seeks. We argue these can (...) be identified deductively by classing behaviour first according to its level of behavioural control. Early animals in our lineage used only reactive production, Vertebrates evolved motivation, and later Primates developed executive control. Behaviour can also be classified by the type of evolutionary benefit it bestows: it can deliver either immediate benefits (food, gametes), improvements in the individual’s position with respect to the world (resource access, social status), or improvements in the ability to secure future benefits (knowledge, skill). Combining history and function implies the existence of seven types of behaviour production systems in human brains responsible for reflexive, instinctual, exploratory, driven, emotional, playful and planned behaviour. Discovering scientifically valid categories of behaviour can provide a fundamental taxonomy and common language for understanding, predicting and changing behaviour, and a way of discovering the organs in the brain––its natural kinds––that are responsible for behaviour. (shrink)

In dynamic system control, cognitive mechanisms and abilities underlying performance may vary depending on the nature of the task. We therefore investigated the effects of system structure and its interaction with cognitive abilities on system control performance. A sample of 127 university students completed a series of different system control tasks that were manipulated in terms of system size and recurrent feedback, either with or without a cognitive load manipulation. Cognitive abilities assessed included reasoning ability, working memory capacity, and cognitive (...) reflection. System size and recurrent feedback affected overall performance as expected. Overall, the results support that cognitive ability is a good predictor of performance in dynamic system control tasks but predictiveness is reduced when the system structure contains recurrent feedback. We discuss this finding from a cognitive processing perspective as well as its implications for individual differences research in dynamic systems. (shrink)

The terms nested sets, partitive frequencies, inside-outside view, and dual processes add little but confusion to our original analysis (Gigerenzer & Hoffrage 1995; 1999). The idea of nested set was introduced because of an oversight; it simply rephrases two of our equations. Representation in terms of chances, in contrast, is a novel contribution yet consistent with our computational analysis System 1.dual process theory” is: Unless the two processes are defined, this distinction can account post hoc for almost everything. In contrast, (...) an ecological view of cognition helps to explain how insight is elicited from the outside (the external representation of information) and, more generally, how cognitive strategies match with environmental structures. (shrink)

Although there is a broad consensus that both the procedural and declarative memory systems play a crucial role in language learning, use, and knowledge, the mapping between linguistic types and memory structures remains underspecified: by default, a dual-route mapping of language systems to memory systems is assumed, with declarative memory handling idiosyncratic lexical knowledge and procedural memory handling rule-governed knowledge of grammar.We experimentally contrast the processing of morphology (case and aspect), syntax (subordination), and lexical semantics (collocations) in a healthy L1 (...) population of Polish, a language rich in form distinctions. We study the processing of these four types under two conditions: a single task condition in which the grammaticality of stimuli was judged and a concurrent task condition in which grammaticality judgments were combined with a digit span task. Dividing attention impedes access to declarative memory while leaving procedural memory unaffected and hence constitutes a test that dissociates which types of linguistic information each long-term memory construct subserves.Our findings confirm the existence of a distinction between lexicon and grammar as a generative, dual-route model would predict, but the distinction is graded, as usage-based models assume: the hypothesized grammar–lexicon opposition appears as a continuum on which grammatical phenomena can be placed as being more or less “ruly” or “idiosyncratic.” However, usage-based models, too, need adjusting as not all types of linguistic knowledge are proceduralized to the same extent. This move away from a simple dichotomy fundamentally changes how we think about memory for language, and hence how we design and interpret behavioral and neuroimaging studies that probe into the nature of language cognition. (shrink)

Regarding awareness as a consistent concept has contributed to the controversy about implicit learning. The present study emphasized the importance of distinguishing aspects of awareness in order to determine whether learning is implicit. By decomposing awareness into awareness of contingencies, of the procedure being a learning task, and of the reinforcing stimuli, it was demonstrated that implicit operant learning modulated pain sensitivity. All of these aspects of awareness were demonstrated to not be necessary for learning. Additionally, discrimination of contingencies was (...) not necessary on different levels of processing as demonstrated by a verbal and a behavioral method. It was demonstrated that explicit cognitive processes about one’s own behavior, impaired learning, even though these cognitions were not immediately related to the learning process. The results of this study are of special interest in the context of pain, since implicit operant learning can explain the gradual development of hypersensitivity in chronic pain. (shrink)