Results for 'computational propaganda'

999 found
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  1.  51
    Automated Influence and the Challenge of Cognitive Security.Sarah Rajtmajer & Daniel Susser - forthcoming - HoTSoS: ACM Symposium on Hot Topics in the Science of Security.
    Advances in AI are powering increasingly precise and widespread computational propaganda, posing serious threats to national security. The military and intelligence communities are starting to discuss ways to engage in this space, but the path forward is still unclear. These developments raise pressing ethical questions, about which existing ethics frameworks are silent. Understanding these challenges through the lens of “cognitive security,” we argue, offers a promising approach.
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  2. Agent-Based Computational Economics: A Constructive Approach to Economic Theory.Leigh Tesfatsion - 2006 - In Leigh Tesfatsion & Kenneth L. Judd (eds.), Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics. Elsevier.
    Economies are complicated systems encompassing micro behaviors, interaction patterns, and global regularities. Whether partial or general in scope, studies of economic systems must consider how to handle difficult real-world aspects such as asymmetric information, imperfect competition, strategic interaction, collective learning, and the possibility of multiple equilibria. Recent advances in analytical and computational tools are permitting new approaches to the quantitative study of these aspects. One such approach is Agent-based Computational Economics (ACE), the computational study of economic processes (...)
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  3. On an Alleged Case of Propaganda: Reply to McKinnon.Sophie R. Allen, Elizabeth Finneron-Burns, Mary Leng, Holly Lawford-Smith, Jane Clare Jones, Rebecca Reilly-Cooper & R. J. Simpson - manuscript
    In her recent paper ‘The Epistemology of Propaganda’ Rachel McKinnon discusses what she refers to as ‘TERF propaganda’. We take issue with three points in her paper. The first is her rejection of the claim that ‘TERF’ is a misogynistic slur. The second is the examples she presents as commitments of so-called ‘TERFs’, in order to establish that radical (and gender critical) feminists rely on a flawed ideology. The third is her claim that standpoint epistemology can be used (...)
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  4. Replicability or Reproducibility? On the Replication Crisis in Computational Neuroscience and Sharing Only Relevant Detail.Marcin Miłkowski, Witold M. Hensel & Mateusz Hohol - 2018 - Journal of Computational Neuroscience 3 (45):163-172.
    Replicability and reproducibility of computational models has been somewhat understudied by “the replication movement.” In this paper, we draw on methodological studies into the replicability of psychological experiments and on the mechanistic account of explanation to analyze the functions of model replications and model reproductions in computational neuroscience. We contend that model replicability, or independent researchers' ability to obtain the same output using original code and data, and model reproducibility, or independent researchers' ability to recreate a model without (...)
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  5. Manufacturing Morality A General Theory of Moral Agency Grounding Computational Implementations: The ACTWith Model.Jeffrey White - 2013 - In Floares (ed.), Computational Intelligence. Nova Publications. pp. 1-65.
    The ultimate goal of research into computational intelligence is the construction of a fully embodied and fully autonomous artificial agent. This ultimate artificial agent must not only be able to act, but it must be able to act morally. In order to realize this goal, a number of challenges must be met, and a number of questions must be answered, the upshot being that, in doing so, the form of agency to which we must aim in developing artificial agents (...)
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  6. Explanation and Description in Computational Neuroscience.David Michael Kaplan - 2011 - Synthese 183 (3):339-373.
    The central aim of this paper is to shed light on the nature of explanation in computational neuroscience. I argue that computational models in this domain possess explanatory force to the extent that they describe the mechanisms responsible for producing a given phenomenon—paralleling how other mechanistic models explain. Conceiving computational explanation as a species of mechanistic explanation affords an important distinction between computational models that play genuine explanatory roles and those that merely provide accurate descriptions or (...)
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  7. 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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  8. Trump, Propaganda, and the Politics of Ressentiment.Cory Wimberly - 2018 - Journal of Speculative Philosophy 32 (1):179.
    This article frames Trump's politics through a genealogy of propaganda, going back to P.T. Barnum in the 19th century and moving through the crowd psychologist Gustave Le Bon and the public relations counsel Edward Bernays in the 20th. This genealogy shows how propaganda was developed as a tool by eager professionals who would hire themselves to the elite to control the masses. Trump’s propaganda presents a break in that he has not only removed professionals from control over (...)
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  9. Computational Entrepreneurship: From Economic Complexities to Interdisciplinary Research.Quan-Hoang Vuong - 2019 - Problems and Perspectives in Management 17 (1):117-129.
    The development of technology is unbelievably rapid. From limited local networks to high speed Internet, from crude computing machines to powerful semi-conductors, the world had changed drastically compared to just a few decades ago. In the constantly renewing process of adapting to such an unnaturally high-entropy setting, innovations as well as entirely new concepts, were often born. In the business world, one such phenomenon was the creation of a new type of entrepreneurship. This paper proposes a new academic discipline of (...)
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  10. Propaganda, Misinformation, and the Epistemic Value of Democracy.Étienne Brown - 2018 - Critical Review 30 (3-4):194-218.
    If citizens are to make enlightened collective decisions, they need to rely on true factual beliefs, but misinformation impairs their ability to do so. Although some cases of misinformation are deliberate and amount to propaganda, cases of inadvertent misinformation are just as problematic in affecting the beliefs and behavior of democratic citizens. A review of empirical evidence suggests that this is a serious problem that cannot entirely be corrected by means of deliberation.
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  11.  58
    Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the Algorithmic.Thomas L. Griffiths, Falk Lieder & Noah D. Goodman - 2015 - Topics in Cognitive Science 7 (2):217-229.
    Marr's levels of analysis—computational, algorithmic, and implementation—have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea (...)
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  12.  37
    Quantifiers and Cognition: Logical and Computational Perspectives.Jakub Szymanik - 2016 - Springer.
    This volume on the semantic complexity of natural language explores the question why some sentences are more difficult than others. While doing so, it lays the groundwork for extending semantic theory with computational and cognitive aspects by combining linguistics and logic with computations and cognition. -/- Quantifier expressions occur whenever we describe the world and communicate about it. Generalized quantifier theory is therefore one of the basic tools of linguistics today, studying the possible meanings and the inferential power of (...)
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  13. Comprehension of Simple Quantifiers: Empirical Evaluation of a Computational Model.Jakub Szymanik & Marcin Zajenkowski - 2010 - Cognitive Science 34 (3):521-532.
    We examine the verification of simple quantifiers in natural language from a computational model perspective. We refer to previous neuropsychological investigations of the same problem and suggest extending their experimental setting. Moreover, we give some direct empirical evidence linking computational complexity predictions with cognitive reality.<br>In the empirical study we compare time needed for understanding different types of quantifiers. We show that the computational distinction between quantifiers recognized by finite-automata and push-down automata is psychologically relevant. Our research improves (...)
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  14.  28
    The Computational and Neural Basis of Cognitive Control: Charted Territory and New Frontiers.Matthew M. Botvinick - 2014 - Cognitive Science 38 (6):1249-1285.
    Cognitive control has long been one of the most active areas of computational modeling work in cognitive science. The focus on computational models as a medium for specifying and developing theory predates the PDP books, and cognitive control was not one of the areas on which they focused. However, the framework they provided has injected work on cognitive control with new energy and new ideas. On the occasion of the books' anniversary, we review computational modeling in the (...)
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  15. Media Argumentation: Dialectic, Persuasion and Rhetoric.Douglas Walton - 2007 - Cambridge University Press.
    Media argumentation is a powerful force in our lives. From political speeches to television commercials to war propaganda, it can effectively mobilize political action, influence the public, and market products. This book presents a new and systematic way of thinking about the influence of mass media in our lives, showing the intersection of media sources with argumentation theory, informal logic, computational theory, and theories of persuasion. Using a variety of case studies that represent arguments that typically occur in (...)
     
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  16.  79
    From Computer Metaphor to Computational Modeling: The Evolution of Computationalism.Marcin Miłkowski - 2018 - Minds and Machines 28 (3):515-541.
    In this paper, I argue that computationalism is a progressive research tradition. Its metaphysical assumptions are that nervous systems are computational, and that information processing is necessary for cognition to occur. First, the primary reasons why information processing should explain cognition are reviewed. Then I argue that early formulations of these reasons are outdated. However, by relying on the mechanistic account of physical computation, they can be recast in a compelling way. Next, I contrast two computational models of (...)
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  17.  41
    Concepts as Semantic Pointers: A Framework and Computational Model.Peter Blouw, Eugene Solodkin, Paul Thagard & Chris Eliasmith - 2016 - Cognitive Science 40 (5):1128-1162.
    The reconciliation of theories of concepts based on prototypes, exemplars, and theory-like structures is a longstanding problem in cognitive science. In response to this problem, researchers have recently tended to adopt either hybrid theories that combine various kinds of representational structure, or eliminative theories that replace concepts with a more finely grained taxonomy of mental representations. In this paper, we describe an alternative approach involving a single class of mental representations called “semantic pointers.” Semantic pointers are symbol-like representations that result (...)
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  18.  44
    A Probabilistic Computational Model of Cross-Situational Word Learning.Afsaneh Fazly, Afra Alishahi & Suzanne Stevenson - 2010 - Cognitive Science 34 (6):1017-1063.
    Words are the essence of communication: They are the building blocks of any language. Learning the meaning of words is thus one of the most important aspects of language acquisition: Children must first learn words before they can combine them into complex utterances. Many theories have been developed to explain the impressive efficiency of young children in acquiring the vocabulary of their language, as well as the developmental patterns observed in the course of lexical acquisition. A major source of disagreement (...)
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  19. The First Computational Theory of Mind and Brain: A Close Look at McCulloch and Pitts' Logical Calculus of Ideas Immanent in Nervous Activity.Gualtiero Piccinini - 2004 - Synthese 141 (2):175-215.
    Despite its significance in neuroscience and computation, McCulloch and Pitts's celebrated 1943 paper has received little historical and philosophical attention. In 1943 there already existed a lively community of biophysicists doing mathematical work on neural networks. What was novel in McCulloch and Pitts's paper was their use of logic and computation to understand neural, and thus mental, activity. McCulloch and Pitts's contributions included (i) a formalism whose refinement and generalization led to the notion of finite automata (an important formalism in (...)
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  20.  68
    Quantifiers in TIME and SPACE. Computational Complexity of Generalized Quantifiers in Natural Language.Jakub Szymanik - 2009 - Dissertation, University of Amsterdam
    In the dissertation we study the complexity of generalized quantifiers in natural language. Our perspective is interdisciplinary: we combine philosophical insights with theoretical computer science, experimental cognitive science and linguistic theories. -/- In Chapter 1 we argue for identifying a part of meaning, the so-called referential meaning (model-checking), with algorithms. Moreover, we discuss the influence of computational complexity theory on cognitive tasks. We give some arguments to treat as cognitively tractable only those problems which can be computed in polynomial (...)
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  21. Computational Explanation in Neuroscience.Gualtiero Piccinini - 2006 - Synthese 153 (3):343-353.
    According to some philosophers, computational explanation is proprietary
    to psychology—it does not belong in neuroscience. But neuroscientists routinely offer computational explanations of cognitive phenomena. In fact, computational explanation was initially imported from computability theory into the science of mind by neuroscientists, who justified this move on neurophysiological grounds. Establishing the legitimacy and importance of computational explanation in neuroscience is one thing; shedding light on it is another. I raise some philosophical questions pertaining to computational explanation and (...)
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  22. The Job of Creating Desire: Propaganda as an Apparatus of Government and Subjectification.Cory Wimberly - 2017 - Journal of Speculative Philosophy 31 (1):101.
    Abstract: This article addresses shortcomings in the way that philosophers and cultural critics have considered propaganda by offering a new genealogical account. Looking at figures such as Marx, Adorno, Marcuse, Habermas, Bourdieu, and Stanley, this article finds that their consideration of propaganda has not necessarily been wrong but has missed some of the most significant and important functions of propaganda. This text draws on archival and published materials from propagandists, most notably Edward Bernays, to elaborate a new (...)
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  23.  16
    Computational Investigations of Multiword Chunks in Language Learning.Stewart M. McCauley & Morten H. Christiansen - 2017 - Topics in Cognitive Science 9 (3):637-652.
    Second-language learners rarely arrive at native proficiency in a number of linguistic domains, including morphological and syntactic processing. Previous approaches to understanding the different outcomes of first- versus second-language learning have focused on cognitive and neural factors. In contrast, we explore the possibility that children and adults may rely on different linguistic units throughout the course of language learning, with specific focus on the granularity of those units. Following recent psycholinguistic evidence for the role of multiword chunks in online language (...)
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  24. Toward a Computational Psycholinguistics of Reference Production.Kees van Deemter, Albert Gatt, Roger P. G. van Gompel & Emiel Krahmer - 2012 - Topics in Cognitive Science 4 (2):166-183.
    This article introduces the topic ‘‘Production of Referring Expressions: Bridging the Gap between Computational and Empirical Approaches to Reference’’ of the journal Topics in Cognitive Science. We argue that computational and psycholinguistic approaches to reference production can benefit from closer interaction, and that this is likely to result in the construction of algorithms that differ markedly from the ones currently known in the computational literature. We focus particularly on determinism, the feature of existing algorithms that is perhaps (...)
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  25. On the Epistemological Analysis of Modeling and Computational Error in the Mathematical Sciences.Nicolas Fillion & Robert M. Corless - 2014 - Synthese 191 (7):1451-1467.
    Interest in the computational aspects of modeling has been steadily growing in philosophy of science. This paper aims to advance the discussion by articulating the way in which modeling and computational errors are related and by explaining the significance of error management strategies for the rational reconstruction of scientific practice. To this end, we first characterize the role and nature of modeling error in relation to a recipe for model construction known as Euler’s recipe. We then describe a (...)
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  26. A Theory of Computational Implementation.Michael Rescorla - 2014 - Synthese 191 (6):1277-1307.
    I articulate and defend a new theory of what it is for a physical system to implement an abstract computational model. According to my descriptivist theory, a physical system implements a computational model just in case the model accurately describes the system. Specifically, the system must reliably transit between computational states in accord with mechanical instructions encoded by the model. I contrast my theory with an influential approach to computational implementation espoused by Chalmers, Putnam, and others. (...)
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  27.  41
    Can Computational Goals Inform Theories of Vision?Barton L. Anderson - 2015 - Topics in Cognitive Science 7 (2):274-286.
    One of the most lasting contributions of Marr's posthumous book is his articulation of the different “levels of analysis” that are needed to understand vision. Although a variety of work has examined how these different levels are related, there is comparatively little examination of the assumptions on which his proposed levels rest, or the plausibility of the approach Marr articulated given those assumptions. Marr placed particular significance on computational level theory, which specifies the “goal” of a computation, its appropriateness (...)
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  28.  25
    A Contrast‐Based Computational Model of Surprise and Its Applications.Luis Macedo & Amílcar Cardoso - 2019 - Topics in Cognitive Science 11 (1):88-102.
    We review our work on a contrast-based computational model of surprise and its applications. The review is contextualized within related research from psychology, philosophy, and particularly artificial intelligence. Influenced by psychological theories of surprise, the model assumes that surprise-eliciting events initiate a series of cognitive processes that begin with the appraisal of the event as unexpected, continue with the interruption of ongoing activity and the focusing of attention on the unexpected event, and culminate in the analysis and evaluation of (...)
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  29.  48
    On Computational Explanations.Anna-Mari Rusanen & Otto Lappi - 2016 - Synthese 193 (12):3931-3949.
    Computational explanations focus on information processing required in specific cognitive capacities, such as perception, reasoning or decision-making. These explanations specify the nature of the information processing task, what information needs to be represented, and why it should be operated on in a particular manner. In this article, the focus is on three questions concerning the nature of computational explanations: What type of explanations they are, in what sense computational explanations are explanatory and to what extent they involve (...)
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  30. Computational Complexity of Polyadic Lifts of Generalized Quantifiers in Natural Language.Jakub Szymanik - 2010 - Linguistics and Philosophy 33 (3):215-250.
    We study the computational complexity of polyadic quantifiers in natural language. This type of quantification is widely used in formal semantics to model the meaning of multi-quantifier sentences. First, we show that the standard constructions that turn simple determiners into complex quantifiers, namely Boolean operations, iteration, cumulation, and resumption, are tractable. Then, we provide an insight into branching operation yielding intractable natural language multi-quantifier expressions. Next, we focus on a linguistic case study. We use computational complexity results to (...)
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  31. A Case Study on Computational Hermeneutics: E. J. Lowe’s Modal Ontological Argument.David Fuenmayor & Christoph Benzmueller - manuscript
    Computers may help us to better understand (not just verify) arguments. In this article we defend this claim by showcasing the application of a new, computer-assisted interpretive method to an exemplary natural-language ar- gument with strong ties to metaphysics and religion: E. J. Lowe’s modern variant of St. Anselm’s ontological argument for the existence of God. Our new method, which we call computational hermeneutics, has been particularly conceived for use in interactive-automated proof assistants. It aims at shedding light on (...)
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  32.  61
    The Perception‐Action Model: Counting Computational Mechanisms.Thor Grünbaum - 2017 - Mind and Language 32 (4):416-445.
    Milner and Goodale's Two Visual Systems Hypothesis is regarded as common ground in recent discussions of visual consciousness. A central part of TVSH is a functional model of vision and action. In this paper, I provide a brief overview of these current discussions and argue that there is ambiguity between a strong and a weak version of PAM. I argue that, given a standard way of individuating computational mechanisms, the available evidence cannot be used to distinguish between these versions. (...)
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  33. A Computational Theory of Perspective and Reference in Narrative.Janyce M. Wiebe & William J. Rapaport - 1988 - In Proceedings of the 26th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. pp. 131-138.
    Narrative passages told from a character's perspective convey the character's thoughts and perceptions. We present a discourse process that recognizes characters'.
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  34.  30
    Idiom Variation: Experimental Data and a Blueprint of a Computational Model.Kristina Geeraert, John Newman & R. Harald Baayen - 2017 - Topics in Cognitive Science 9 (3):653-669.
    Corpus surveys have shown that the exact forms with which idioms are realized are subject to variation. We report a rating experiment showing that such alternative realizations have varying degrees of acceptability. Idiom variation challenges processing theories associating idioms with fixed multi-word form units, fixed configurations of words, or fixed superlemmas, as they do not explain how it can be that speakers produce variant forms that listeners can still make sense of. A computational model simulating comprehension with naive discriminative (...)
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  35. Steps Toward a Computational Metaphysics.Branden Fitelson & Edward N. Zalta - 2007 - Journal of Philosophical Logic 36 (2):227-247.
    In this paper, the authors describe their initial investigations in computational metaphysics. Our method is to implement axiomatic metaphysics in an automated reasoning system. In this paper, we describe what we have discovered when the theory of abstract objects is implemented in PROVER9 (a first-order automated reasoning system which is the successor to OTTER). After reviewing the second-order, axiomatic theory of abstract objects, we show (1) how to represent a fragment of that theory in PROVER9's first-order syntax, and (2) (...)
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  36. Computational and Biological Analogies for Understanding Fine-Tuned Parameters in Physics.Clément Vidal - 2010 - Foundations of Science 15 (4):375 - 393.
    In this philosophical paper, we explore computational and biological analogies to address the fine-tuning problem in cosmology. We first clarify what it means for physical constants or initial conditions to be fine-tuned. We review important distinctions such as the dimensionless and dimensional physical constants, and the classification of constants proposed by Lévy-Leblond. Then we explore how two great analogies, computational and biological, can give new insights into our problem. This paper includes a preliminary study to examine the two (...)
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  37.  13
    A Computational Investigation of Sources of Variability in Sentence Comprehension Difficulty in Aphasia.Paul Mätzig, Shravan Vasishth, Felix Engelmann, David Caplan & Frank Burchert - 2018 - Topics in Cognitive Science 10 (1):161-174.
    We present a computational evaluation of three hypotheses about sources of deficit in sentence comprehension in aphasia: slowed processing, intermittent deficiency, and resource reduction. The ACT-R based Lewis and Vasishth model is used to implement these three proposals. Slowed processing is implemented as slowed execution time of parse steps; intermittent deficiency as increased random noise in activation of elements in memory; and resource reduction as reduced spreading activation. As data, we considered subject vs. object relative sentences, presented in a (...)
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  38.  52
    Media Argumentation: Dialectic, Persuasion and Rhetoric.Douglas Walton - 2007 - Cambridge University Press.
    Media argumentation is a powerful force in our lives. From political speeches to television commercials to war propaganda, it can effectively mobilize political action, influence the public, and market products. This book presents a new and systematic way of thinking about the influence of mass media in our lives, showing the intersection of media sources with argumentation theory, informal logic, computational theory, and theories of persuasion. Using a variety of case studies that represent arguments that typically occur in (...)
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  39.  63
    Situatedness and Embodiment of Computational Systems.Marcin Miłkowski - 2017 - Entropy 19 (4):162.
    In this paper, the role of the environment and physical embodiment of computational systems for explanatory purposes will be analyzed. In particular, the focus will be on cognitive computational systems, understood in terms of mechanisms that manipulate semantic information. It will be argued that the role of the environment has long been appreciated, in particular in the work of Herbert A. Simon, which has inspired the mechanistic view on explanation. From Simon’s perspective, the embodied view on cognition seems (...)
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  40. Feeling and Representing: Computational Theory and the Modularity of Affect.Louis C. Charland - 1995 - Synthese 105 (3):273-301.
    In this paper I review some leading developments in the empirical theory of affect. I argue that (1) affect is a distinct perceptual representation governed system, and (2) that there are significant modular factors in affect. The paper concludes with the observation thatfeeler (affective perceptual system) may be a natural kind within cognitive science. The main purpose of the paper is to explore some hitherto unappreciated connections between the theory of affect and the computational theory of mind.
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  41.  35
    Computational Neuroscience and Localized Neural Function.Daniel C. Burnston - 2016 - Synthese 193 (12):3741-3762.
    In this paper I criticize a view of functional localization in neuroscience, which I call “computational absolutism”. “Absolutism” in general is the view that each part of the brain should be given a single, univocal function ascription. Traditional varieties of absolutism posit that each part of the brain processes a particular type of information and/or performs a specific task. These function attributions are currently beset by physiological evidence which seems to suggest that brain areas are multifunctional—that they process distinct (...)
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  42.  23
    A Computational Evaluation of Sentence Processing Deficits in Aphasia.Umesh Patil, Sandra Hanne, Frank Burchert, Ria De Bleser & Shravan Vasishth - 2016 - Cognitive Science 40 (1):5-50.
    Individuals with agrammatic Broca's aphasia experience difficulty when processing reversible non-canonical sentences. Different accounts have been proposed to explain this phenomenon. The Trace Deletion account attributes this deficit to an impairment in syntactic representations, whereas others propose that the underlying structural representations are unimpaired, but sentence comprehension is affected by processing deficits, such as slow lexical activation, reduction in memory resources, slowed processing and/or intermittent deficiency, among others. We test the claims of two processing accounts, slowed processing and intermittent deficiency, (...)
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  43. Computational Mechanisms and Models of Computation.Marcin Miłkowski - 2014 - Philosophia Scientiæ 18:215-228.
    In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. -/- In this paper, I claim that mechanistic accounts of computation should allow for a broad variation of (...)
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  44.  8
    Sculpting Computational‐Level Models.Mark Blokpoel - 2018 - Topics in Cognitive Science 10 (3):641-648.
    In this commentary, I advocate for strict relations between Marr's levels of analysis. Under a strict relationship, each level is exactly implemented by the subordinate level. This yields two benefits. First, it brings consistency for multilevel explanations. Second, similar to how a sculptor chisels away superfluous marble, a modeler can chisel a computational-level model by applying constraints. By sculpting the model, one restricts the set of possible algorithmic- and implementational-level theories.
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  45.  63
    Mechanistic Computational Individuation Without Biting the Bullet.Nir Fresco & Marcin Miłkowski - 2019 - British Journal for the Philosophy of Science:axz005.
    Is the mathematical function being computed by a given physical system determined by the system’s dynamics? This question is at the heart of the indeterminacy of computation phenomenon (Fresco et al. [unpublished]). A paradigmatic example is a conventional electrical AND-gate that is often said to compute conjunction, but it can just as well be used to compute disjunction. Despite the pervasiveness of this phenomenon in physical computational systems, it has been discussed in the philosophical literature only indirectly, mostly with (...)
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  46.  89
    Computationalism: Still the Only Game in Town: A Reply to Swiatczak’s “Conscious Representations: An Intractable Problem for the Computational Theory of Mind”. [REVIEW]David Davenport - 2012 - Minds and Machines 22 (3):183-190.
    Abstract Mental representations, Swiatczak (Minds Mach 21:19–32, 2011) argues, are fundamentally biochemical and their operations depend on consciousness; hence the computational theory of mind, based as it is on multiple realisability and purely syntactic operations, must be wrong. Swiatczak, however, is mistaken. Computation, properly understood, can afford descriptions/explanations of any physical process, and since Swiatczak accepts that consciousness has a physical basis, his argument against computationalism must fail. Of course, we may not have much idea how consciousness (itself a (...)
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  47. Are Turing Machines Platonists? Inferentialism and the Computational Theory of Mind.Jon Cogburn & Jason Megil - 2010 - Minds and Machines 20 (3):423-439.
    We first discuss Michael Dummett’s philosophy of mathematics and Robert Brandom’s philosophy of language to demonstrate that inferentialism entails the falsity of Church’s Thesis and, as a consequence, the Computational Theory of Mind. This amounts to an entirely novel critique of mechanism in the philosophy of mind, one we show to have tremendous advantages over the traditional Lucas-Penrose argument.
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  48. The Nature of Computational Things.Franck Varenne - 2013 - In Frédéric Migayrou Brayer & Marie-Ange (eds.), Naturalizing Architecture. Orléans: HYX Editions. pp. 96-105.
    Architecture often relies on mathematical models, if only to anticipate the physical behavior of structures. Accordingly, mathematical modeling serves to find an optimal form given certain constraints, constraints themselves translated into a language which must be homogeneous to that of the model in order for resolution to be possible. Traditional modeling tied to design and architecture thus appears linked to a topdown vision of creation, of the modernist, voluntarist and uniformly normative type, because usually (mono)functionalist. One available instrument of calculation/representation/prescription (...)
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    How Computational Models Predict the Behavior of Complex Systems.John Symons & Fabio Boschetti - 2013 - Foundations of Science 18 (4):809-821.
    In this paper, we argue for the centrality of prediction in the use of computational models in science. We focus on the consequences of the irreversibility of computational models and on the conditional or ceteris paribus, nature of the kinds of their predictions. By irreversibility, we mean the fact that computational models can generally arrive at the same state via many possible sequences of previous states. Thus, while in the natural world, it is generally assumed that physical (...)
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    Reconciling Two Computational Models of Working Memory in Aging.Violette Hoareau, Benoît Lemaire, Sophie Portrat & Gaën Plancher - 2016 - Topics in Cognitive Science 8 (1):264-278.
    It is well known that working memory performance changes with age. Two recent computational models of working memory, TBRS* and SOB-CS, developed from young adults WM performances are opposed regarding the postulated causes of forgetting, namely time-based decay and interference for TBRS* and SOB-CS, respectively. In the present study, these models are applied on a set of complex span data produced by young and older adults. As expected, these models are unable to account for the older adult data. An (...)
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