Results for 'bi-modular systems'

974 found
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  1.  12
    Non-Monotonic Reasoning: Logical Architecture and Philosophical Applications.Yao-Hua Tan - 1992 - Amsterdam, Netherlands: Drukkerij Elinkwijk.
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  2.  13
    An Ellulian analysis of propaganda in the context of generative AI.Xiaomei Bi, Xingyuan Su & Xiaoyan Liu - 2024 - Ethics and Information Technology 26 (3):1-11.
    The application of generative artificial intelligence (GenAI) technologies in the field of propaganda influences information creation, dissemination, and reception, and introduces new ethical challenges. This paper revisits the philosophical discourses of Jacques Ellul on technology and propaganda, placing them within the context of the rise of today’s generative AI technologies. Ellul identified the First Industrial Revolution as the initial juncture in the history of human technology that formed technique as a social phenomenon, which subsequently shaped the nature of propaganda as (...)
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  3.  41
    A duality between Pawlak's knowledge representation systems and bi-consequence systems.Dimiter Vakarelov - 1995 - Studia Logica 55 (1):205 - 228.
    A duality between Pawlak's knowledge representation systems and certain information systems of logical type, called bi-consequence systems is established. As an application a first-order characterization of some informational relations is given and a completeness theorem for the corresponding modal logic INF is proved. It is shown that INF possesses finite model property and hence is decidable.
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  4.  33
    Judicial knowledge-enhanced magnitude-aware reasoning for numerical legal judgment prediction.Sheng Bi, Zhiyao Zhou, Lu Pan & Guilin Qi - 2023 - Artificial Intelligence and Law 31 (4):773-806.
    Legal Judgment Prediction (LJP) is an essential component of legal assistant systems, which aims to automatically predict judgment results from a given criminal fact description. As a vital subtask of LJP, researchers have paid little attention to the numerical LJP, i.e., the prediction of imprisonment and penalty. Existing methods ignore numerical information in the criminal facts, making their performances far from satisfactory. For instance, the amount of theft varies, as do the prison terms and penalties. The major challenge is (...)
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  5.  13
    Enterprise Strategic Management From the Perspective of Business Ecosystem Construction Based on Multimodal Emotion Recognition.Wei Bi, Yongzhen Xie, Zheng Dong & Hongshen Li - 2022 - Frontiers in Psychology 13.
    Emotion recognition is an important part of building an intelligent human-computer interaction system and plays an important role in human-computer interaction. Often, people express their feelings through a variety of symbols, such as words and facial expressions. A business ecosystem is an economic community based on interacting organizations and individuals. Over time, they develop their capabilities and roles together and tend to develop themselves in the direction of one or more central enterprises. This paper aims to study a multimodal ER (...)
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  6.  46
    The measure of biological age in plant modular systems.A. Ritterbusch - 1990 - Acta Biotheoretica 38 (2):113-124.
    Phytomorphology — if concerned with development — often concentrates on correlative changes of form and neglects the aspects of age, time and clock, although the plant's spatial and temporal organisation are intimately interconnected. Common age as measured in physical time by a physical process is compared to biological age as measured by a biological clock based on a biological process. A typical example for a biological clock on the organ level is, for example, a shoot. Its biological age is measured (...)
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  7. Is there only one innate modular system for spatial navigation?Alexandre Duval - 2024 - Behavioral and Brain Sciences 47:e125.
    Spelke convincingly argues that we should posit six innate modular systems beyond the periphery (i.e., beyond low-level perception and motor control). I focus on the case of spatial navigation (Ch. 3) to claim that there remain powerful considerations in favor of positing additional innate, nonperipheral modules. This opens the door to stronger forms of nativism and nonperipheral modularism than Spelke's.
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  8. Atomistic learning in non-modular systems.Pierre Poirier - 2005 - Philosophical Psychology 18 (3):313-325.
    We argue that atomistic learning?learning that requires training only on a novel item to be learned?is problematic for networks in which every weight is available for change in every learning situation. This is potentially significant because atomistic learning appears to be commonplace in humans and most non-human animals. We briefly review various proposed fixes, concluding that the most promising strategy to date involves training on pseudo-patterns along with novel items, a form of learning that is not strictly atomistic, but which (...)
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  9.  24
    The Construction of Bi-Modal Systems.Arata Ishimoto & Yoshimi Fujikawa - 1969 - Kagaku Tetsugaku 2:5-17.
  10.  34
    The essential opacity of modular systems: Why even connectionism cannot give complete formal accounts of cognition.Marten J. den Uyl - 1988 - Behavioral and Brain Sciences 11 (1):56-57.
  11. The modularity of the motor system.Myrto Mylopoulos - 2021 - Philosophical Explorations 24 (3):376-393.
    In this paper, I make a case for the modularity of the motor system. I start where many do in discussions of modularity, by considering the extent to which the motor system is cognitively penetrable, i.e., the extent to which its processing and outputs are causally influenced, in a semantically coherent way, by states of central cognition. I present some empirical findings from a range of sensorimotor adaptation studies that strongly suggest that there are limits to such influence under certain (...)
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  12.  41
    Modularity: Understanding the Development and Evolution of Natural Complex Systems.Werner Callebaut & Diego Rasskin-Gutman (eds.) - 2005 - MIT Press.
    This collection broadens the scientific discussion of modularity by bringing together experts from a variety of disciplines, including artificial life, ...
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  13.  10
    How Does the Parent–Adolescent Relationship Affect Adolescent Internet Addiction? Parents’ Distinctive Influences.Huaiyuan Qi, Qinhong Kang & Cuihua Bi - 2022 - Frontiers in Psychology 13.
    Although previous research has demonstrated that parent–adolescent relationships have a significant effect on adolescent Internet Addiction, the mechanisms underlying these associations and parental differences in these effects have received insufficient attention. We investigated the mediating role of Perceived Social Support and Dual System of Self-Control in the relationship between Father-Adolescent Relationships/Mother-Adolescent Relationships and adolescent IA, as well as the differences in the effects of FAR and MAR. A cross-sectional survey of 732 Chinese adolescents was conducted using the Adolescent Pathological Internet (...)
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  14.  20
    Cultural Religion Pedagogy.Muhiddin Okumuşlar & Sümeyra Bi̇leci̇k - 2019 - Cumhuriyet İlahiyat Dergisi 23 (3):1279-1292.
    Many factors like the structure of the society, political conditions, and social structure of a country are useful in determining pedagogical approaches. One of them is culture, which is influential on the way of life of the individual, as well as thinking and learning styles. This requires the examination of the relationship between culture and pedagogy. It is possible to discuss cultural, multicultural, and intercultural pedagogical approaches regarding the relationship between pedagogy and culture. The socio-political agenda of a country is (...)
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  15. The modularity of dynamic systems.Teed Rockwell - 1998 - Colloquia Manilana 6.
    To some degree, Fodor's claim that Cognitive science divides the mind into modules tells us more about the minds doing the studying than the mind being studied. The knowledge game is played by analyzing an object of study into parts, and then figuring out how those parts are related to each other. This is the method regardless of whether the object being studied is a mind or a solar system. If a module is just another name for a part, then (...)
     
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  16. Modular and hierarchical learning systems.Michael I. Jordan & Robert A. Jacobs - 1995 - In Michael A. Arbib (ed.), Handbook of Brain Theory and Neural Networks. MIT Press. pp. 579--582.
  17.  30
    Modular structurality and emergent functionality within knowledge representation systems.Adam Fedyniuk - 2016 - Semina Scientiarum 15:77-87.
    There are various approaches to ontology metamodelling, and the notion of biologically inspired modular knowledge representation systems can provide insight in the workings of such phenomena as emergent properties of network structures. What is more relevant from knowledge engineering standpoint, such approach could provide innovation and enhancement of the level of expression as well as overall functionality of modular ontologies. To do so, one needs to find biological structures that would be the basis for modularity on different (...)
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  18. Modularity, and the psychoevolutionary theory of emotion.Paul E. Griffiths - 1990 - Biology and Philosophy 5 (2):175-196.
    It is unreasonable to assume that our pre-scientific emotion vocabulary embodies all and only those distinctions required for a scientific psychology of emotion. The psychoevolutionary approach to emotion yields an alternative classification of certain emotion phenomena. The new categories are based on a set of evolved adaptive responses, or affect-programs, which are found in all cultures. The triggering of these responses involves a modular system of stimulus appraisal, whose evoluations may conflict with those of higher-level cognitive processes. Whilst the (...)
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  19. Towards ontologies for formalizing modularization and communication in large software systems.Daniel Oberle, Steffen Lamparter, S. Grimm, D. Vrandečić, S. Staab & A. Gangemi - 2006 - Applied ontology 1 (2):163-202.
    Large software systems are modularized in order to improve manageability. The parts of a software system communicate in order to achieve the desired functionality. To better understand, develop, manage, and maintain the resulting complexity, this paper presents a framework of ontologies. The ontologies range from very general, foundational ones to ontologies that elucidate the specificities of particular modularization and communication paradigms. We support two specific paradigms. First, we define an ontology for software components that may be used in traditional (...)
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  20.  17
    Modularity, antimodularity and explanation in complex systems.Luca Rivelli - 2015 - Dissertation, University of Paris 1 Panthéon-Sorbonne
    This work is mainly concerned with the notion of hierarchical modularity and its use in explaining structure and dynamical behavior of complex systems by means of hierarchical modular models, as well as with a concept of my proposal, antimodularity, tied to the possibility of the algorithmic detection of hierarchical modularity. Specifically, I highlight the pragmatic bearing of hierarchical modularity on the possibility of scientific explanation of complex systems, that is, systems which, according to a chosen basic (...)
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  21.  42
    Understanding the Emergence of Modularity in Neural Systems.John A. Bullinaria - 2007 - Cognitive Science 31 (4):673-695.
    Modularity in the human brain remains a controversial issue, with disagreement over the nature of the modules that exist, and why, when, and how they emerge. It is a natural assumption that modularity offers some form of computational advantage, and hence evolution by natural selection has translated those advantages into the kind of modular neural structures familiar to cognitive scientists. However, simulations of the evolution of simplified neural systems have shown that, in many cases, it is actually non- (...) architectures that are most efficient. In this paper, the relevant issues are discussed and a series of simulations are presented that reveal crucial dependencies on the details of the learning algorithms and tasks that are being modelled, and the importance of taking into account known physical brain constraints, such as the degree of neural connectivity. A pattern is established which provides one explanation of why modularity should emerge reliably across a range of neural processing tasks. (shrink)
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  22. Commentary on "the modularity of dynamic systems".Teed Rockwell - unknown
    1. Throughout the paper, and especially in the section called "LISP vs. DST", I worried that there was not enough focus on EXPLANATION. For the real question, it seems to me, is not whether some dynamical system can implement human cognition, but whether the dynamical description of the system is more explanatorily potent than a computational/representational one. Thus we know, for example, that a purely physical specification can fix a system capable of computing any LISP function. But from this it (...)
     
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  23.  13
    Modular robotic systems: Methods and algorithms for abstraction, planning, control, and synchronization.Hossein Ahmadzadeh & Ellips Masehian - 2015 - Artificial Intelligence 223 (C):27-64.
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  24.  37
    Modularity in neural systems and localization of function.Carlo Umiltà - 2003 - In L. Nadel (ed.), Encyclopedia of Cognitive Science. Nature Publishing Group.
  25.  43
    Modular mind or unitary system: A duck-rabbit effect.Gillian Cohen - 1984 - Behavioral and Brain Sciences 7 (1):71-72.
  26.  43
    Modularity, and the Psychoevolutionary Theory of Emotion.P. E. Griffiths - 1990 - Biology and Philosophy 5 (2):175.
    It is unreasonable to assume that our pre-scientific emotion vocabulary embodies all and only those distinctions required for a scientific psychology of emotion. The psychoevolutionary approach to emotion yields an alternative classification of certain emotion phenomena. The new categories are based on a set of evolved adaptive responses, or affect-programs, which are found in all cultures. The triggering of these responses involves a modular system of stimulus appraisal, whose evoluations may conflict with those of higher-level cognitive processes. Whilst the (...)
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  27. Bodily Systems and the Modular Structure of the Human Body.Barry Smith, Igor Papakin & Katherine Munn - 2003 - Artificial Intelligence in Medicine (Lecture Notes on Artificial Intelligence 2780) 9:86-90.
    Medical science conceives the human body as a system comprised of many subsystems at a variety of levels. At the highest level are bodily systems proper, such as the endocrine system, which are central to our understanding of human anatomy, and play a key role in diagnosis and in dynamic modeling as well as in medical pedagogy and computer visualization. But there is no explicit definition of what a bodily system is; such informality is acceptable in documentation created for (...)
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  28. Commentary on "the modularity of dynamic systems".Andy Clark - unknown
    1. Throughout the paper, and especially in the section called "LISP vs. DST", I worried that there was not enough focus on EXPLANATION. For the real question, it seems to me, is not whether some dynamical system can implement human cognition, but whether the dynamical description of the system is more explanatorily potent than a computational/representational one. Thus we know, for example, that a purely physical specification can fix a system capable of computing any LISP function. But from this it (...)
     
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  29.  13
    A Modular Neural Network Decision Support System in EMG Diagnosis.C. I. Christodoulou, C. S. Pattichis & W. F. Fincham - 1998 - Journal of Intelligent Systems 8 (1-2):99-144.
  30. Training of modular neural net systems.P. Gallinari - 1995 - In Michael A. Arbib (ed.), Handbook of Brain Theory and Neural Networks. MIT Press. pp. 582--585.
  31.  15
    The logical structure of modular semantic theories of software systems.Nicola Angius & Petros Stefaneas - 2024 - Metaphilosophy 55 (3):440-456.
    This paper studies the structure of semantic theories over modular computational systems and applies the algebraic Theory of Institutions to provide a logical representation of such theories. A modular semantic theory is here defined by a cluster of semantic theories, each for a single program's module, and by a set of relations connecting models of different semantic theories. A semantic theory of a single module is provided in terms of the set of ∑‐models mapped from the category (...)
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  32.  27
    Modularity: Contextual interactions and the tractability of nonmodular systems.Sam Glucksberg - 1985 - Behavioral and Brain Sciences 8 (1):14-15.
  33.  22
    Impression formation and the modular mind: The associated systems theory.Donal E. Carlston - 1992 - In Leonard L. Martin & Abraham Tesser (eds.), The Construction of Social Judgments. Lawrence Erlbaum. pp. 301--341.
  34. Modularity in cognition: Framing the debate.H. Clark Barrett & Robert Kurzban - 2006 - Psychological Review 113 (3):628-647.
    Modularity has been the subject of intense debate in the cognitive sciences for more than 2 decades. In some cases, misunderstandings have impeded conceptual progress. Here the authors identify arguments about modularity that either have been abandoned or were never held by proponents of modular views of the mind. The authors review arguments that purport to undermine modularity, with particular attention on cognitive architecture, development, genetics, and evolution. The authors propose that modularity, cleanly defined, provides a useful framework for (...)
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  35.  8
    Subjektive Freiheit und soziales System: Positionen der kritischen Gesellschaftstheorie von Rousseau bis zur Habermas/Luhmann-Kontroverse.Smail Rapic - 2008 - Freiburg: Alber.
  36.  48
    An axiom system for the modular logic.Jerzy Kotas - 1967 - Studia Logica 21 (1):17 - 38.
  37.  30
    Modularity and Mental Architecture.Philip Robbins - 2013 - WIREs Cognitive Science 4 (6):641-648.
    Debates about the modularity of cognitive architecture have been ongoing for at least the past three decades, since the publication of Fodor’s landmark book The Modularity of Mind (1983). According to Fodor, modularity is essentially tied to informational encapsulation, and as such is only found in the relatively low-level cognitive systems responsible for perception and language. According to Fodor’s critics in the evolutionary psychology camp, modularity simply reflects the fine-grained functional specialization dictated by natural selection, and it characterizes virtually (...)
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  38. Enzymatic computation and cognitive modularity.H. Clark Barrett - 2005 - Mind and Language 20 (3):259-87.
    Currently, there is widespread skepticism that higher cognitive processes, given their apparent flexibility and globality, could be carried out by specialized computational devices, or modules. This skepticism is largely due to Fodor’s influential definition of modularity. From the rather flexible catalogue of possible modular features that Fodor originally proposed has emerged a widely held notion of modules as rigid, informationally encapsulated devices that accept highly local inputs and whose opera- tions are insensitive to context. It is a mistake, however, (...)
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  39. Modularity and relevance: How can a massively modular mind be flexible and context-sensitive.Dan Sperber - 2005 - In Peter Carruthers, Stephen Laurence & Stephen P. Stich (eds.), The Innate Mind: Structure and Contents. New York, US: Oxford University Press on Demand. pp. 53.
    The claim that the human cognitive system tends to allocate resources to the processing of available inputs according to their expected relevance is at the basis of relevance theory. The main thesis of this chapter is that this allocation can be achieved without computing expected relevance. When an input meets the input condition of a given modular procedure, it gives this procedure some initial level of activation. Input-activated procedures are in competition for the energy resources that would allow them (...)
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  40. Discovering Empirical Theories of Modular Software Systems. An Algebraic Approach.Nicola Angius & Petros Stefaneas - 2016 - In Vincent C. Müller (ed.), Computing and philosophy: Selected papers from IACAP 2014. Cham: Springer. pp. 99-115.
    This paper is concerned with the construction of theories of software systems yielding adequate predictions of their target systems’ computations. It is first argued that mathematical theories of programs are not able to provide predictions that are consistent with observed executions. Empirical theories of software systems are here introduced semantically, in terms of a hierarchy of computational models that are supplied by formal methods and testing techniques in computer science. Both deductive top-down and inductive bottom-up approaches in (...)
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  41. Pain: Modularity and Cognitive Constitution.Błażej Skrzypulec - forthcoming - The British Journal for the Philosophy of Science.
    Discussions concerning the modularity of the pain system have been focused on questions regarding the cognitive penetrability of pain mechanisms. It has been claimed that phenomena such as placebo analgesia demonstrate that the pain system is cognitively penetrated; therefore, it is not encapsulated from central cognition. However, important arguments have been formulated which aim to show that cognitive penetrability does not in fact entail a lack of modularity of the pain system. This paper offers an alternative way to reject the (...)
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  42. Uniform and Modular Sequent Systems for Description Logics.Tim Lyon & Jonas Karge - 2022 - In Ofer Arieli, Martin Homola, Jean Christoph Jung & Marie-Laure Mugnier (eds.), Proceedings of the 35th International Workshop on Description Logics (DL 2022).
    We introduce a framework that allows for the construction of sequent systems for expressive description logics extending ALC. Our framework not only covers a wide array of common description logics, but also allows for sequent systems to be obtained for extensions of description logics with special formulae that we call "role relational axioms." All sequent systems are sound, complete, and possess favorable properties such as height-preserving admissibility of common structural rules and height-preserving invertibility of rules.
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  43.  18
    On abstract modular inference systems and solvers.Yuliya Lierler & Miroslaw Truszczynski - 2016 - Artificial Intelligence 236 (C):65-89.
  44. Structuralism, Modular Construction, and “Grid” As Universal Instruments for Building Designs.Klodjan Xhexhi - 2023 - International Journal of Advanced Natural Sciences and Engineering Researches 7:198-197.
    Structuralism can be defined as an important concept of using “units” as elements of form and space-giving, where the whole form is made not only up of a “texture”, a certain flexible grid, or an algorithm of shape-giving, but it depends also on the relationships created and how people use it. The hypothesis of this study is that “Modular Construction” can also have an aesthetically pleasing outlook and that modular housing can definitely have increasing importance in the future. (...)
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  45.  13
    Modularity. Understanding the Development and Evolution of Natural Complex Systems. Werner Callebaut & Diego Rasskin-Gutman (eds.). [REVIEW]Linda Van Speybroeck - 2005 - Philosophica 76 (2).
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  46. Practical reasoning in a modular mind.Peter Carruthers - 2004 - Mind and Language 19 (3):259-278.
    This paper starts from an assumption defended in the author's previous work. This is that distinctivelyhuman flexible and creative theoretical thinking can be explained in terms of the interactions of a variety of modular systems, with the addition of just a few amodular components and dispositions. On the basis of that assumption it is argued that distinctively human practical reasoning, too, can be understood in modular terms. The upshot is that there is nothing in the human psyche (...)
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  47.  72
    Modular Sequent Calculi for Classical Modal Logics.David R. Gilbert & Paolo Maffezioli - 2015 - Studia Logica 103 (1):175-217.
    This paper develops sequent calculi for several classical modal logics. Utilizing a polymodal translation of the standard modal language, we are able to establish a base system for the minimal classical modal logic E from which we generate extensions in a modular manner. Our systems admit contraction and cut admissibility, and allow a systematic proof-search procedure of formal derivations.
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  48. Modular argumentation for modelling legal doctrines in common law of contract.Phan Minh Dung & Phan Minh Thang - 2009 - Artificial Intelligence and Law 17 (3):167-182.
    To create a programming environment for contract dispute resolution, we propose an extension of assumption-based argumentation into modular assumption-based argumentation in which different modules of argumentation representing different knowledge bases for reasoning about beliefs and facts and for representation and reasoning with the legal doctrines could be built and assembled together. A distinct novel feature of modular argumentation in compare with other modular logic-based systems like Prolog is that it allows references to different semantics in the (...)
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  49. Towards ontologies for formalizing modularization and communication in large software systems.Daniel Oberle, Steffen Lamparter, Stephan Grimm, D. Vrandeči&Cacute, Steffen Staab & Aldo Gangemi - 2006 - Applied ontology 1 (2):163-202.
     
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  50.  7
    Modularity.Emma Borg - 2004 - In Minimal semantics. New York: Oxford University Press.
    An introduction to the notion of modularity of mind and an argument as to why only formal semantic theories are compatible with the claim that semantic comprehension is the product of a modular system. This chapter also looks at some initial challenges to formal semantics stemming from the apparent place of pragmatic reasoning in our grasp of meaning. These include arguments concerning the nature of speech acts, the analysis of implicatures, word learning, and ambiguity.
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