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  1. Against Fragmentation.Aaron Norby - 2014 - Thought: A Journal of Philosophy 3 (1):30-38.
    I criticize the idea that theories of ‘fragmented’ or ‘compartmentalized’ belief (as found in, e.g., Lewis 1982, Egan 2008) can help to account for the puzzling phenomena they are often taken to account for. After introducing fragmentationalism and a paradigm case that purportedly motivates it, I criticize the view primarily on the grounds that the models and explanations it offers are at best trivial—as witnessed by examples of over-generation—and should be seen as merely re-describing in figurative terms the phenomena it (...)
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  • What Levels of Explanation in the Behavioural Sciences?Giuseppe Boccignone & Roberto Cordeschi (eds.) - 2015 - Frontiers Media SA.
    Complex systems are to be seen as typically having multiple levels of organization. For instance, in the behavioural and cognitive sciences, there has been a long lasting trend, promoted by the seminal work of David Marr, putting focus on three distinct levels of analysis: the computational level, accounting for the What and Why issues, the algorithmic and the implementational levels specifying the How problem. However, the tremendous developments in neuroscience knowledge about processes at different scales of organization together with the (...)
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  • Studying Strategies and Types of Players: Experiments, Logics and Cognitive Models.Sujata Ghosh & Rineke Verbrugge - 2018 - Synthese 195 (10):4265-4307.
    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 (...)
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  • Unification Strategies in Cognitive Science.Marcin Miłkowski - 2016 - Studies in Logic, Grammar and Rhetoric 48 (1):13–33.
    Cognitive science is an interdisciplinary conglomerate of various research fields and disciplines, which increases the risk of fragmentation of cognitive theories. However, while most previous work has focused on theoretical integration, some kinds of integration may turn out to be monstrous, or result in superficially lumped and unrelated bodies of knowledge. In this paper, I distinguish theoretical integration from theoretical unification, and propose some analyses of theoretical unification dimensions. Moreover, two research strategies that are supposed to lead to unification are (...)
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  • Modeling Triple-Tasking Without Customized Cognitive Control.Jelmer P. Borst, Niels A. Taatgen & Hedderik Van Rijn - 2009 - In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society.
  • Cognitive Science.Paul Thagard - 2008 - Stanford Encyclopedia of Philosophy.
    Cognitive science is the interdisciplinary investigation of mind and intelligence, embracing psychology, neuroscience, anthropology, artificial intelligence, and philosophy. There are many important philosophical questions related to this investigation, but this short chapter will focus on the following three. What is the nature of the explanations and theories developed in cognitive science? What are the relations among the five disciplines that comprise cognitive science? What are the implications of cognitive science research for general issues in the philosophy of science? I will (...)
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  • Cognitive Science.Thagard Paul - forthcoming - Stanford Encyclopedia of Philosophy.
  • Beyond Single‐Level Accounts: The Role of Cognitive Architectures in Cognitive Scientific Explanation.Richard P. Cooper & David Peebles - 2015 - Topics in Cognitive Science 7 (2):243-258.
    We consider approaches to explanation within the cognitive sciences that begin with Marr's computational level or Marr's implementational level and argue that each is subject to fundamental limitations which impair their ability to provide adequate explanations of cognitive phenomena. For this reason, it is argued, explanation cannot proceed at either level without tight coupling to the algorithmic and representation level. Even at this level, however, we argue that additional constraints relating to the decomposition of the cognitive system into a set (...)
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  • WikiSilo: A Self-Organizing, Crowd Sourcing System for Interdisciplinary Science [Supporting Paper].David Pierre Leibovitz, Robert L. West & Mike Belanger - manuscript
    WikiSilo is a tool for theorizing across interdisciplinary fields such as Cognitive Science, and provides a vocabulary for talking about the problems of doing so. It can be used to demonstrate that a particular cognitive theory is complete and coherent at multiple levels of discourse, and commensurable with and relevant to a wider domain of cognition. WikiSilo is also a minimalist theory and methodology for effectively doing science. WikiSilo is simultaneously similar to and distinct, as well as integrated and separated (...)
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  • A Perceptual Account of Symbolic Reasoning.David Landy, Colin Allen & Carlos Zednik - 2014 - Frontiers in Psychology 5.
    People can be taught to manipulate symbols according to formal mathematical and logical rules. Cognitive scientists have traditionally viewed this capacity—the capacity for symbolic reasoning—as grounded in the ability to internally represent numbers, logical relationships, and mathematical rules in an abstract, amodal fashion. We present an alternative view, portraying symbolic reasoning as a special kind of embodied reasoning in which arithmetic and logical formulae, externally represented as notations, serve as targets for powerful perceptual and sensorimotor systems. Although symbolic reasoning often (...)
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  • The Acquisition of Robust and Flexible Cognitive Skills.Niels A. Taatgen, David Huss, Daniel Dickison & John R. Anderson - 2008 - Journal of Experimental Psychology: General 137 (3):548-565.
  • Expert Interpretation of Bar and Line Graphs: The Role of Graphicacy in Reducing the Effect of Graph Format.David Peebles & Nadia Ali - 2015 - Frontiers in Psychology 6.
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  • Between Language and Consciousness: Linguistic Qualia, Awareness, and Cognitive Models.Piotr Konderak - 2017 - Studies in Logic, Grammar and Rhetoric 48 (1):285-302.
    The main goal of the paper is to present a putative role of consciousness in language capacity. The paper contrasts the two approaches characteristic for cognitive semiotics and cognitive science. Language is treated as a mental phenomenon and a cognitive faculty. The analysis of language activity is based on the Chalmers’ distinction between the two forms of consciousness: phenomenal and psychological. The approach is seen as an alternative to phenomenological analyses typical for cognitive semiotics. Further, a cognitive model of the (...)
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  • Introduction to the Issue on Computational Models of Natural Language.John Hale & David Reitter - 2013 - Topics in Cognitive Science 5 (3):388-391.
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  • Neural Computation and the Computational Theory of Cognition.Gualtiero Piccinini & Sonya Bahar - 2013 - Cognitive Science 37 (3):453-488.
    We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous (...)
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  • Toward a Unified View of Cognitive Control.Dario D. Salvucci & Niels A. Taatgen - 2011 - Topics in Cognitive Science 3 (2):227-230.
    Allen Newell (1973) once observed that psychology researchers were playing “twenty questions with nature,” carving up human cognition into hundreds of individual phenomena but shying away from the difficult task of integrating these phenomena with unifying theories. We argue that research on cognitive control has followed a similar path, and that the best approach toward unifying theories of cognitive control is that proposed by Newell, namely developing theories in computational cognitive architectures. Threaded cognition, a recent theory developed within the ACT-R (...)
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  • A Canonical Theory of Dynamic Decision-Making.John Fox, Richard P. Cooper & David W. Glasspool - 2013 - Frontiers in Psychology 4.
  • The Locus of the Gratton Effect in Picture–Word Interference.Leendert van Maanen & Hedderik van Rijn - 2010 - Topics in Cognitive Science 2 (1):168-180.
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  • An Individual's Rate of Forgetting Is Stable Over Time but Differs Across Materials.Florian Sense, Friederike Behrens, Rob R. Meijer & Hedderik Rijn - 2016 - Topics in Cognitive Science 8 (1):305-321.
    One of the goals of computerized tutoring systems is to optimize the learning of facts. Over a hundred years of declarative memory research have identified two robust effects that can improve such systems: the spacing and the testing effect. By making optimal use of both and adjusting the system to the individual learner using cognitive models based on declarative memory theories, such systems consistently outperform traditional methods. This adjustment process is driven by a continuously updated estimate of the rate of (...)
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  • Uncertainty Without All the Doubt.Aaron Norby - 2015 - Mind and Language 30 (1):70-94.
    I investigate whether degreed beliefs are able to play the predictive, explanatory, and modeling roles that they are frequently taken to play. The investigation focuses on evidence—both from sources familiar in epistemology as well as recent work in behavioral economics and cognitive psychology—of variability in agents' apparent degrees of belief. Although such variability has been noticed before, there has been little philosophical discussion of its breadth or of the psychological mechanisms underlying it. Once these are appreciated, the inadequacy of degrees (...)
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  • Criteria for the Design and Evaluation of Cognitive Architectures.Sashank Varma - 2011 - Cognitive Science 35 (7):1329-1351.
    Cognitive architectures are unified theories of cognition that take the form of computational formalisms. They support computational models that collectively account for large numbers of empirical regularities using small numbers of computational mechanisms. Empirical coverage and parsimony are the most prominent criteria by which architectures are designed and evaluated, but they are not the only ones. This paper considers three additional criteria that have been comparatively undertheorized. (a) Successful architectures possess subjective and intersubjective meaning, making cognition comprehensible to individual cognitive (...)
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  • Integration and Reuse in Cognitive Skill Acquisition.Dario D. Salvucci - 2013 - Cognitive Science 37 (5):829-860.
    Previous accounts of cognitive skill acquisition have demonstrated how procedural knowledge can be obtained and transformed over time into skilled task performance. This article focuses on a complementary aspect of skill acquisition, namely the integration and reuse of previously known component skills. The article posits that, in addition to mechanisms that proceduralize knowledge into more efficient forms, skill acquisition requires tight integration of newly acquired knowledge and previously learned knowledge. Skill acquisition also benefits from reuse of existing knowledge across disparate (...)
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  • Symbol Interdependency in Symbolic and Embodied Cognition.Max M. Louwerse - 2011 - Topics in Cognitive Science 3 (2):273-302.
    Whether computational algorithms such as latent semantic analysis (LSA) can both extract meaning from language and advance theories of human cognition has become a topic of debate in cognitive science, whereby accounts of symbolic cognition and embodied cognition are often contrasted. Albeit for different reasons, in both accounts the importance of statistical regularities in linguistic surface structure tends to be underestimated. The current article gives an overview of the symbolic and embodied cognition accounts and shows how meaning induction attributed to (...)
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  • The Past, Present, and Future of Cognitive Architectures.Niels Taatgen & John R. Anderson - 2010 - Topics in Cognitive Science 2 (4):693-704.
    Cognitive architectures are theories of cognition that try to capture the essential representations and mechanisms that underlie cognition. Research in cognitive architectures has gradually moved from a focus on the functional capabilities of architectures to the ability to model the details of human behavior, and, more recently, brain activity. Although there are many different architectures, they share many identical or similar mechanisms, permitting possible future convergence. In judging the quality of a particular cognitive model, it is pertinent to not just (...)
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  • Why Cognitive Science Needs Philosophy and Vice Versa.Paul Thagard - 2009 - Topics in Cognitive Science 1 (2):237-254.
    Contrary to common views that philosophy is extraneous to cognitive science, this paper argues that philosophy has a crucial role to play in cognitive science with respect to generality and normativity. General questions include the nature of theories and explanations, the role of computer simulation in cognitive theorizing, and the relations among the different fields of cognitive science. Normative questions include whether human thinking should be Bayesian, whether decision making should maximize expected utility, and how norms should be established. These (...)
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  • Exploring the Functional Advantages of Spatial and Visual Cognition From an Architectural Perspective.Scott D. Lathrop, Samuel Wintermute & John E. Laird - 2011 - Topics in Cognitive Science 3 (4):796-818.
    We present a general cognitive architecture that tightly integrates symbolic, spatial, and visual representations. A key means to achieving this integration is allowing cognition to move freely between these modes, using mental imagery. The specific components and their integration are motivated by results from psychology, as well as the need for developing a functional and efficient implementation. We discuss functional benefits that result from the combination of multiple content-based representations and the specialized processing units associated with them. Instantiating this theory, (...)
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  • Cognitive Control: Componential and Yet Emergent.Ion Juvina - 2011 - Topics in Cognitive Science 3 (2):242-246.
    In this commentary, I will argue that the componential and emergent views of cognitive control as defined by Cooper (2010) do not necessarily oppose each other, and I will try to make a case for their interdependence. First, I will use the construct of cognitive inhibition—one of the main componential control functions mentioned in the target articles—to illustrate my line of reasoning. Then, I will comment on how some of the target articles, each from a different perspective, bring arguments in (...)
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  • Utility-Based Generation of Referring Expressions.Markus Guhe - 2012 - Topics in Cognitive Science 4 (2):306-329.
    This paper presents two cognitive models that simulate the production of referring expressions in the iMAP task—a task-oriented dialog. One general model is based on Dale and Reiter’s (1995)incremental algorithm, and the other is a simple template model that has a higher correlation with the data but is specifically geared toward the properties of the iMAP task. The property of the iMAP task environment that is modeled here is that the color feature is unreliable for identifying referents while other features (...)
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  • When, What, and How Much to Reward in Reinforcement Learning-Based Models of Cognition.Christian P. Janssen & Wayne D. Gray - 2012 - Cognitive Science 36 (2):333-358.
    Reinforcement learning approaches to cognitive modeling represent task acquisition as learning to choose the sequence of steps that accomplishes the task while maximizing a reward. However, an apparently unrecognized problem for modelers is choosing when, what, and how much to reward; that is, when (the moment: end of trial, subtask, or some other interval of task performance), what (the objective function: e.g., performance time or performance accuracy), and how much (the magnitude: with binary, categorical, or continuous values). In this article, (...)
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  • RACE/A: An Architectural Account of the Interactions Between Learning, Task Control, and Retrieval Dynamics.Leendert van Maanen, Hedderik van Rijn & Niels Taatgen - 2012 - Cognitive Science 36 (1):62-101.
    This article discusses how sequential sampling models can be integrated in a cognitive architecture. The new theory Retrieval by Accumulating Evidence in an Architecture (RACE/A) combines the level of detail typically provided by sequential sampling models with the level of task complexity typically provided by cognitive architectures. We will use RACE/A to model data from two variants of a picture–word interference task in a psychological refractory period design. These models will demonstrate how RACE/A enables interactions between sequential sampling and long-term (...)
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  • How WM Load Influences Linguistic Processing in Adults: A Computational Model of Pronoun Interpretation in Discourse.Jacolien Rij, Hedderik Rijn & Petra Hendriks - 2013 - Topics in Cognitive Science 5 (3):564-580.
    This paper presents a study of the effect of working memory load on the interpretation of pronouns in different discourse contexts: stories with and without a topic shift. We discuss a computational model (in ACT-R, Anderson, 2007) to explain how referring expressions are acquired and used. On the basis of simulations of this model, it is predicted that WM constraints only affect adults' pronoun resolution in stories with a topic shift, but not in stories without a topic shift. This latter (...)
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  • Set as an Instance of a Real-World Visual-Cognitive Task.Enkhbold Nyamsuren & Niels A. Taatgen - 2013 - Cognitive Science 37 (1):146-175.
    Complex problem solving is often an integration of perceptual processing and deliberate planning. But what balances these two processes, and how do novices differ from experts? We investigate the interplay between these two in the game of SET. This article investigates how people combine bottom-up visual processes and top-down planning to succeed in this game. Using combinatorial and mixed-effect regression analysis of eye-movement protocols and a cognitive model of a human player, we show that SET players deploy both bottom-up and (...)
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  • The Influence of Activation Level on Belief Bias in Relational Reasoning.Adrian P. Banks - 2013 - Cognitive Science 37 (3):544-577.
    A novel explanation of belief bias in relational reasoning is presented based on the role of working memory and retrieval in deductive reasoning, and the influence of prior knowledge on this process. It is proposed that belief bias is caused by the believability of a conclusion in working memory which influences its activation level, determining its likelihood of retrieval and therefore its effect on the reasoning process. This theory explores two main influences of belief on the activation levels of these (...)
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  • A Moderate Approach to Embodied Cognitive Science.Alvin I. Goldman - 2012 - Review of Philosophy and Psychology 3 (1):71-88.
    Many current programs for cognitive science sail under the banner of “embodied cognition.” These programs typically seek to distance themselves from standard cognitive science. The present proposal for a conception of embodied cognition is less radical than most, indeed, quite compatible with many versions of traditional cognitive science. Its rationale is based on two elements, each of which is theoretically plausible and empirically well-founded. The first element invokes the idea of “bodily formats,” i.e., representational codes primarily utilized in forming interoceptive (...)
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  • The Developmental Paradox of False Belief Understanding: A Dual-System Solution.L. C. De Bruin & A. Newen - 2014 - Synthese 191 (3).
    We explore the developmental paradox of false belief understanding. This paradox follows from the claim that young infants already have an understanding of false belief, despite the fact that they consistently fail the elicited-response false belief task. First, we argue that recent proposals to solve this paradox are unsatisfactory because they (i) try to give a full explanation of false belief understanding in terms of a single system, (ii) fail to provide psychological concepts that are sufficiently fine-grained to capture the (...)
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  • Embodied Spatial Cognition.J. Gregory Trafton & Anthony M. Harrison - 2011 - Topics in Cognitive Science 3 (4):686-706.
    We present a spatial system called Specialized Egocentrically Coordinated Spaces embedded in an embodied cognitive architecture (ACT-R Embodied). We show how the spatial system works by modeling two different developmental findings: gaze-following and Level 1 perspective taking. The gaze-following model is based on an experiment by Corkum and Moore (1998), whereas the Level 1 visual perspective-taking model is based on an experiment by Moll and Tomasello (2006). The models run on an embodied robotic system.
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  • Discovering the Sequential Structure of Thought.John R. Anderson & Jon M. Fincham - 2014 - Cognitive Science 38 (2):322-352.
    Multi-voxel pattern recognition techniques combined with Hidden Markov models can be used to discover the mental states that people go through in performing a task. The combined method identifies both the mental states and how their durations vary with experimental conditions. We apply this method to a task where participants solve novel mathematical problems. We identify four states in the solution of these problems: Encoding, Planning, Solving, and Respond. The method allows us to interpret what participants are doing on individual (...)
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  • Goal‐Proximity Decision‐Making.Vladislav D. Veksler, Wayne D. Gray & Michael J. Schoelles - 2013 - Cognitive Science 37 (4):757-774.
    Reinforcement learning (RL) models of decision-making cannot account for human decisions in the absence of prior reward or punishment. We propose a mechanism for choosing among available options based on goal-option association strengths, where association strengths between objects represent previously experienced object proximity. The proposed mechanism, Goal-Proximity Decision-making (GPD), is implemented within the ACT-R cognitive framework. GPD is found to be more efficient than RL in three maze-navigation simulations. GPD advantages over RL seem to grow as task difficulty is increased. (...)
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  • Mechanisms for Robust Cognition.Matthew M. Walsh & Kevin A. Gluck - 2015 - Cognitive Science 39 (6):1131-1171.
    To function well in an unpredictable environment using unreliable components, a system must have a high degree of robustness. Robustness is fundamental to biological systems and is an objective in the design of engineered systems such as airplane engines and buildings. Cognitive systems, like biological and engineered systems, exist within variable environments. This raises the question, how do cognitive systems achieve similarly high degrees of robustness? The aim of this study was to identify a set of mechanisms that enhance robustness (...)
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  • SAwSu: An Integrated Model of Associative and Reinforcement Learning.Vladislav D. Veksler, Christopher W. Myers & Kevin A. Gluck - 2014 - Cognitive Science 38 (3):580-598.
    Successfully explaining and replicating the complexity and generality of human and animal learning will require the integration of a variety of learning mechanisms. Here, we introduce a computational model which integrates associative learning (AL) and reinforcement learning (RL). We contrast the integrated model with standalone AL and RL models in three simulation studies. First, a synthetic grid-navigation task is employed to highlight performance advantages for the integrated model in an environment where the reward structure is both diverse and dynamic. The (...)
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  • Towards an Integration of Two Aspects of Semiosis – A Cognitive Semiotic Perspective.Piotr Konderak - 2021 - Sign Systems Studies 49 (1-2):132-165.
    Meaning-making processes, understood hierarchically, in line with the Semiotic Hierarchy framework, change on various timescales. To account for and predict these changes, one can take a cognitive view on semiosis. I adopt an interdis-ciplinary approach combining semiotic studies and cognitive studies in an attempt to account for meaning-making activity and to predict the course of semiosis. In this context, I consider meaning-making activity as shaped by both “external” (to a semiotic system) as well as “internal” factors. I also show how (...)
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  • Computational Rationality: Linking Mechanism and Behavior Through Bounded Utility Maximization.Richard L. Lewis, Andrew Howes & Satinder Singh - 2014 - Topics in Cognitive Science 6 (2):279-311.
    We propose a framework for including information-processing bounds in rational analyses. It is an application of bounded optimality (Russell & Subramanian, 1995) to the challenges of developing theories of mechanism and behavior. The framework is based on the idea that behaviors are generated by cognitive mechanisms that are adapted to the structure of not only the environment but also the mind and brain itself. We call the framework computational rationality to emphasize the incorporation of computational mechanism into the definition of (...)
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  • Linguistics and the Explanatory Economy.Gabe Dupre - 2019 - Synthese 199 (Suppl 1):177-219.
    I present a novel, collaborative, methodology for linguistics: what I call the ‘explanatory economy’. According to this picture, multiple models/theories are evaluated based on the extent to which they complement one another with respect to data coverage. I show how this model can resolve a long-standing worry about the methodology of generative linguistics: that by creating too much distance between data and theory, the empirical credentials of this research program are tarnished. I provide justifications of such methodologically central distinctions as (...)
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  • 'Theory of Mind' in Animals: Ways to Make Progress.Elske Vaart & Charlotte K. Hemelrijk - 2012 - Synthese (3):1-20.
    Whether any non-human animal can attribute mental states to others remains the subject of extensive debate. This despite the fact that several species have behaved as if they have a ‘theory of mind’ in various behavioral tasks. In this paper, we review the reasons of skeptics for their doubts: That existing experimental setups cannot distinguish between ‘mind readers’ and ‘behavior readers’, that results that seem to indicate ‘theory of mind’ may come from studies that are insufficiently controlled, and that our (...)
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  • LOT, CTM, and the Elephant in the Room.Susan Schneider - 2009 - Synthese 170 (2):235 - 250.
    According to the language of thought (LOT) approach and the related computational theory of mind (CTM), thinking is the processing of symbols in an inner mental language that is distinct from any public language. Herein, I explore a deep problem at the heart of the LOT/CTM program—it has yet to provide a plausible conception of a mental symbol.
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  • Can Resources Save Rationality? ‘Anti-Bayesian’ Updating in Cognition and Perception.Eric Mandelbaum, Isabel Won, Steven Gross & Chaz Firestone - 2020 - Behavioral and Brain Sciences 143:e16.
    Resource rationality may explain suboptimal patterns of reasoning; but what of “anti-Bayesian” effects where the mind updates in a direction opposite the one it should? We present two phenomena — belief polarization and the size-weight illusion — that are not obviously explained by performance- or resource-based constraints, nor by the authors’ brief discussion of reference repulsion. Can resource rationality accommodate them?
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  • Neurodemocracy: Self-Organization of the Embodied Mind.Linus Huang - 2017 - Dissertation, University of Sydney
    This thesis contributes to a better conceptual understanding of how self-organized control works. I begin by analyzing the control problem and its solution space. I argue that the two prominent solutions offered by classical cognitive science (centralized control with rich commands, e.g., the Fodorian central systems) and embodied cognitive science (distributed control with simple commands, such as the subsumption architecture by Rodney Brooks) are merely two positions in a two-dimensional solution space. I outline two alternative positions: one is distributed control (...)
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  • Signic Knowledge: Its Niche in Semiotics and its Various Aspects.Liqin Cao & Yiqiang Jin - 2021 - Semiotica 2021 (239):225-242.
    Signic knowledge is a crucial link without which the sign as a phenomenon tumbles to the ground. This topic, however, can hardly be incorporated by any existing theory of semiotics. Under the framework of “the theory of intentional sign,” signic knowledge can find its proper niche as an element of the “context” of a sign process. This niche furnishes a good basis on which to investigate the various aspects of signic knowledge, like its role, nature, origin, and life. Signic knowledge (...)
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  • Levels and Norm-Development: A Phenomenological Approach to Enactive-Ecological Norms of Action and Perception.Miguel A. Sepúlveda-Pedro - 2020 - Frontiers in Psychology 11.
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  • Five-Year-Olds’ Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study.Burcu Arslan, Niels A. Taatgen & Rineke Verbrugge - 2017 - Frontiers in Psychology 8.