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  1. ID + MD = OD Towards a Fundamental Algorithm for Consciousness.Thomas McGrath - manuscript
    The Algorithm described in this short paper is a simplified formal representation of consciousness that may be applied in the fields of Psychology and Artificial Intelligence. -/- Click on the download link to read full essay...
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  2. Introduction to a Systemic Theory of Meaning (July 2014 update).Christophe Menant - manuscript
    Information and Meaning are present everywhere around us and within ourselves. Specific studies have been implemented in order to link information and meaning: - Semiotics - Phenomenology - Analytic Philosophy - Psychology No general coverage is available for the notion of meaning. We propose to complement this lack by a systemic approach to meaning generation.
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  3. Introduction to a Systemic Theory of Meaning - March 2020 update.Christophe Menant - manuscript
    Information and meaning are present everywhere around us and within ourselves. Specific studies have been implemented to link information and meaning (Linguistic, Biosemiotic, Psychology, Psychiatry, Cognition, Artificial Intelligence... ). No general coverage is available for the notion of meaning. We propose to complement this lack by a system approach to meaning generation in an evolutionary background. That short paper is a summary of the system approach where a Meaning Generator System (MGS) based on internal constraint satisfaction has been introduced. The (...)
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  4. Space, and not Time, Provides the Basic Structure of Memory.Sara Aronowitz & Lynn Nadel - forthcoming - In Lynn Nadel & Sara Aronowitz (eds.), Space, Time, and Memory. Oxford University Press.
    When entering an environment, animals – including humans – tend to consult their memories to determine what they know about the place. This information is useful to determine: is this place safe? And what happens next? In this chapter, we argue on both empirical and conceptual grounds that memory is largely organized by space. Spatial relations determine what is recalled and which experiences are combined in generalizations. Time does not play an analogous role. We show that space and time in (...)
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  5. Real Sparks of Artificial Intelligence and the Importance of Inner Interpretability.Alex Grzankowski - forthcoming - Inquiry: An Interdisciplinary Journal of Philosophy.
    The present paper looks at one of the most thorough articles on the intelligence of GPT, research conducted by engineers at Microsoft. Although there is a great deal of value in their work, I will argue that, for familiar philosophical reasons, their methodology, ‘Black-box Interpretability’ is wrongheaded. But there is a better way. There is an exciting and emerging discipline of ‘Inner Interpretability’ (also sometimes called ‘White-box Interpretability’) that aims to uncover the internal activations and weights of models in order (...)
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  6. Making AI Intelligible: Philosophical Foundations. By Herman Cappelen and Josh Dever. [REVIEW]Nikhil Mahant - forthcoming - Philosophical Quarterly.
    Linguistic outputs generated by modern machine-learning neural net AI systems seem to have the same contents—i.e., meaning, semantic value, etc.—as the corresponding human-generated utterances and texts. Building upon this essential premise, Herman Cappelen and Josh Dever's Making AI Intelligible sets for itself the task of addressing the question of how AI-generated outputs have the contents that they seem to have (henceforth, ‘the question of AI Content’). In pursuing this ambitious task, the book makes several high-level, framework observations about how a (...)
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  7. Confronting value-based argumentation frameworks with people’s assessment of argument strength.Gustavo A. Bodanza & Esteban Freidin - 2023 - Argument and Computation 14 (3):247-273.
    We reported a series of experiments carried out to confront the underlying intuitions of value-based argumentation frameworks (VAFs) with the intuitions of ordinary people. Our goal was twofold. On the one hand, we intended to test VAF as a descriptive theory of human argument evaluations. On the other, we aimed to gain new insights from empirical data that could serve to improve VAF as a normative model. The experiments showed that people’s acceptance of arguments deviates from VAF’s semantics and is (...)
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  8. Toward biologically plausible artificial vision.Mason Westfall - 2023 - Behavioral and Brain Sciences 46:e290.
    Quilty-Dunn et al. argue that deep convolutional neural networks (DCNNs) optimized for image classification exemplify structural disanalogies to human vision. A different kind of artificial vision – found in reinforcement-learning agents navigating artificial three-dimensional environments – can be expected to be more human-like. Recent work suggests that language-like representations substantially improves these agents’ performance, lending some indirect support to the language-of-thought hypothesis (LoTH).
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  9. Mind as Machine: The Influence of Mechanism on the Conceptual Foundations of the Computer Metaphor.Pavel Baryshnikov - 2022 - RUDN Journal of Philosophy 26 (4):755-769.
    his article will focus on the mechanistic origins of the computer metaphor, which forms the conceptual framework for the methodology of the cognitive sciences, some areas of artificial intelligence and the philosophy of mind. The connection between the history of computing technology, epistemology and the philosophy of mind is expressed through the metaphorical dictionaries of the philosophical discourse of a particular era. The conceptual clarification of this connection and the substantiation of the mechanistic components of the computer metaphor is the (...)
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  10. Interprétabilité et explicabilité de phénomènes prédits par de l’apprentissage machine.Christophe Denis & Franck Varenne - 2022 - Revue Ouverte d'Intelligence Artificielle 3 (3-4):287-310.
    Le déficit d’explicabilité des techniques d’apprentissage machine (AM) pose des problèmes opérationnels, juridiques et éthiques. Un des principaux objectifs de notre projet est de fournir des explications éthiques des sorties générées par une application fondée sur de l’AM, considérée comme une boîte noire. La première étape de ce projet, présentée dans cet article, consiste à montrer que la validation de ces boîtes noires diffère épistémologiquement de celle mise en place dans le cadre d’une modélisation mathéma- tique et causale d’un phénomène (...)
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  11. Tekoälyn varhaishistoriaa: laskevia koneita ja spirituaalisia automaatteja.Markku Roinila - 2021 - In Panu Raatikainen (ed.), Tekoäly, ihminen ja yhteiskunta : filosofisia näkökulmia. Helsinki: Gaudeamus. pp. 21-37.
    Hahmottelen tässä artikkelissa tekoälyn historiaa varhaismodernin filosofian aikakaudella 1600–1700-luvuilla. Esittelemäni aiheet ovat hieman erillisiä toisistaan, mutta yhteistä niille on ajatus komputaatiosta tai automaatiosta, eräänlaisesta mekaanisesta laskemisesta tai toiminnasta, jota voi pitää tekoälyn varhaisena lähtökohtana. -/- On kuitenkin huomattava, että pelkkä komputaatio eli informaation käsittely sinänsä ei riitä tekoälylle – kaikkia näitä pyrkimyksiä leimaa tietynlainen epistemologinen optimismi: automatisoidun ajattelun avulla uskotaan saatavan enemmän laadukasta tietoa ja kenties myös uudenlaisia ajatuksia, kun ajatteluprosessi tulee sujuvammaksi. Tekoälyn varhaishistoria liittyy siis nimenomaan inhimillisen ajattelun mekanisoimiseen (...)
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  12. AGI and the Knight-Darwin Law: why idealized AGI reproduction requires collaboration.Samuel Alexander - 2020 - Agi.
    Can an AGI create a more intelligent AGI? Under idealized assumptions, for a certain theoretical type of intelligence, our answer is: “Not without outside help”. This is a paper on the mathematical structure of AGI populations when parent AGIs create child AGIs. We argue that such populations satisfy a certain biological law. Motivated by observations of sexual reproduction in seemingly-asexual species, the Knight-Darwin Law states that it is impossible for one organism to asexually produce another, which asexually produces another, and (...)
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  13. The Archimedean trap: Why traditional reinforcement learning will probably not yield AGI.Samuel Allen Alexander - 2020 - Journal of Artificial General Intelligence 11 (1):70-85.
    After generalizing the Archimedean property of real numbers in such a way as to make it adaptable to non-numeric structures, we demonstrate that the real numbers cannot be used to accurately measure non-Archimedean structures. We argue that, since an agent with Artificial General Intelligence (AGI) should have no problem engaging in tasks that inherently involve non-Archimedean rewards, and since traditional reinforcement learning rewards are real numbers, therefore traditional reinforcement learning probably will not lead to AGI. We indicate two possible ways (...)
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  14. DNAOS for KREMMS: A distributed platform for knowledge resource entitlement, modeling, management, and sharing.Andre Cusson - 2020 - Journal of Knowledge Structures and Systems 1 (1):117-133.
    This article is a knowledge technology case study of DNAOS, a distributed platform for Knowledge Resource Entitlement, Modeling, Management, and Sharing (KREMMS). Some historical aspects of its design, development, and release are briefly discussed, after which the DNAOS technology is commented upon from the specific viewpoint of KREMMS. At the core of this platform is the conception of knowledge as a natural phenomenon, which conception is reflected in the ontology of this technology: Fundamental knowledge structures and structuring principles, believed to (...)
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  15. Werden Hominoide oder Androiden die Erde zerstören? -Eine Rezension von "Wie man einen Geist erschafft" von Ray Kurzweil (How to Create a Mind) von Ray Kurzweil (2012) (Rezension überarbeitet 2019).Michael Richard Starks - 2020 - In Willkommen in der Hölle auf Erden: Babys, Klimawandel, Bitcoin, Kartelle, China, Demokratie, Vielfalt, Dysgenie, Gleichheit, Hacker, Menschenrechte, Islam, Liberalismus, Wohlstand, Internet, Chaos, Hunger, Krankheit, Gewalt, Künstliche Intelligenz, Krieg. Reality Press. pp. 158-170.
    Vor einigen, Jahren habe ich den Punkt erreicht, an dem ich normalerweise aus dem Titel eines Buches oder zumindest aus den Kapiteltiteln erzähle, welche philosophischen Fehler gemacht werden und wie häufig. Bei nominell wissenschaftlichen Arbeiten können diese weitgehend auf bestimmte Kapitel beschränkt sein, die philosophisch werden oder versuchen, allgemeine Schlussfolgerungen über die Bedeutung oder langfristige-Bedeutung des Werkes zuziehen. Normalerweise sind die wissenschaftlichen Fakten jedoch großzügig mit philosophischem Kauderwelsch darüber, was diese Tatsachen bedeuten, verwogen. Die klaren Unterscheidungen, die Wittgenstein vor etwa (...)
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  16. 인간이나 안드로이드가 지구를 파괴 할 것인가? — '마음 만드는 법'의 검토 (How to Create a Mind) Ray Kurzweil (2010).Michael Richard Starks - 2020 - In 지구상의 지옥에 오신 것을 환영합니다 : 아기, 기후 변화, 비트 코인, 카르텔, 중국, 민주주의, 다양성, 역학, 평등, 해커, 인권, 이슬람, 자유주의, 번영, 웹, 혼돈, 기아, 질병, 폭력, 인공 지능, 전쟁. Las Vegas, NV USA: Reality Press. pp. 172-186.
    몇 년전, 저는 보통 책의 제목이나 적어도 장 제목에서 어떤 종류의 철학적 실수를 저지르고 얼마나 자주 알 수 있는지 를 알 수 있는 지점에 도달했습니다. 명목상 과학적 작품의 경우, 이들은 크게 철학적 왁스 또는 의미 또는 긴에 대한 일반적인 결론을 그리려는 특정 장으로 제한 될 수있다-작업의기간 의의. 그러나 일반적으로 사실의 과학적 문제는 이러한 사실이 무엇을 의미하는지에 관해서는 철학적 횡설수설과 관대하게 얽혀있다. Wittgenstein이 약 80 년 전에 과학 문제와 다양한 언어 게임에 의한 설명 사이에 설명 한 명확한 차이점은 거의 고려되지 않으므로 (...)
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  17. Gli ominoidi o gli androidi distruggeranno la Terra? Una recensione di Come Creare una Mente (How to Create a Mind) di Ray Kurzweil (2012) (recensione rivista nel 2019).Michael Richard Starks - 2020 - In Benvenuti all'inferno sulla Terra: Bambini, Cambiamenti climatici, Bitcoin, Cartelli, Cina, Democrazia, Diversità, Disgenetica, Uguaglianza, Pirati Informatici, Diritti umani, Islam, Liberalismo, Prosperità, Web, Caos, Fame, Malattia, Violenza, Intellige. Las Vegas, NV, USA: Reality Press. pp. 150-162.
    Alcuni anni fa, ho raggiunto il punto in cui di solito posso dire dal titolo di un libro, o almeno dai titoli dei capitoli, quali tipi di errori filosofici saranno fatti e con quale frequenza. Nel caso di opere nominalmente scientifiche queste possono essere in gran parte limitate a determinati capitoli che sono filosofici o cercanodi trarre conclusioni generali sul significato o sul significato a lungoterminedell'opera. Normalmente però le questioni scientifiche di fatto sono generosamente intrecciate con incomprodellami filosofici su ciò (...)
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  18. Andy Clark and his Critics.Matteo Colombo, Elizabeth Irvine & Mog Stapleton (eds.) - 2019 - New York, NY: Oxford University Press.
    In this volume, a range of high-profile researchers in philosophy of mind, philosophy of cognitive science, and empirical cognitive science, critically engage with Clark's work across the themes of: Extended, Embodied, Embedded, Enactive, and Affective Minds; Natural Born Cyborgs; and Perception, Action, and Prediction. Daniel Dennett provides a foreword on the significance of Clark's work, and Clark replies to each section of the book, thus advancing current literature with original contributions that will form the basis for new discussions, debates and (...)
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  19. Será que Hominoids ou Androids Destroem a Terra? — uma revisão de Como Criar Uma Mente (How to Create a Mind) por Ray Kurzweil (2012) (revisão revisada 2019).Michael Richard Starks - 2019 - In Delírios Utópicos Suicidas no Século XXI Filosofia, Natureza Humana e o Colapso da Civilization- Artigos e Comentários 2006-2019 5ª edição. Las Vegas, NV USA: Reality Press. pp. 155-167.
    Alguns anos atrás, cheguei ao ponto onde eu normalmente pode dizer a partir do título de um livro, ou pelo menos a partir dos títulos do capítulo, que tipos de erros filosóficos serão feitas e com que freqüência. No caso de obras nominalmente científicas, estas podem ser largamente restritas a certos capítulos que enceram filosóficos ou tentam tirar conclusões gerais sobre o significado ou significado a longo prazo do trabalho. Normalmente entretanto as matérias científicas do fato são misturado generosa com (...)
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  20. The realizers and vehicles of mental representation.Zoe Drayson - 2018 - Studies in History and Philosophy of Science Part A 68:80-87.
    The neural vehicles of mental representation play an explanatory role in cognitive psychology that their realizers do not. In this paper, I argue that the individuation of realizers as vehicles of representation restricts the sorts of explanations in which they can participate. I illustrate this with reference to Rupert’s (2011) claim that representational vehicles can play an explanatory role in psychology in virtue of their quantity or proportion. I propose that such quantity-based explanatory claims can apply only to realizers and (...)
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  21. Heterogeneous Proxytypes Extended: Integrating Theory-like Representations and Mechanisms with Prototypes and Exemplars.Antonio Lieto - 2018 - In Advances in Intelligent Systems and Computing, Springer. Springer.
    The paper introduces an extension of the proposal according to which conceptual representations in cognitive agents should be intended as heterogeneous proxytypes. The main contribution of this paper is in that it details how to reconcile, under a heterogeneous representational perspective, different theories of typicality about conceptual representation and reasoning. In particular, it provides a novel theoretical hypothesis - as well as a novel categorization algorithm called DELTA - showing how to integrate the representational and reasoning assumptions of the theory-theory (...)
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  22. The Knowledge Level in Cognitive Architectures: Current Limitations and Possible Developments.Antonio Lieto, Christian Lebiere & Alessandro Oltramari - 2018 - Cognitive Systems Research:1-42.
    In this paper we identify and characterize an analysis of two problematic aspects affecting the representational level of cognitive architectures (CAs), namely: the limited size and the homogeneous typology of the encoded and processed knowledge. We argue that such aspects may constitute not only a technological problem that, in our opinion, should be addressed in order to build arti cial agents able to exhibit intelligent behaviours in general scenarios, but also an epistemological one, since they limit the plausibility of the (...)
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  23. Computational Dynamics of Natural Information Morphology, Discretely Continuous.Gordana Dodig-Crnkovic - 2017 - Philosophies 2 (4):23.
    This paper presents a theoretical study of the binary oppositions underlying the mechanisms of natural computation understood as dynamical processes on natural information morphologies. Of special interest are the oppositions of discrete vs. continuous, structure vs. process, and differentiation vs. integration. The framework used is that of computing nature, where all natural processes at different levels of organisation are computations over informational structures. The interactions at different levels of granularity/organisation in nature, and the character of the phenomena that unfold through (...)
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  24. Dual PECCS: A Cognitive System for Conceptual Representation and Categorization.Antonio Lieto, Daniele Radicioni & Valentina Rho - 2017 - Journal of Experimental and Theoretical Artificial Intelligence 29 (2):433-452.
    In this article we present an advanced version of Dual-PECCS, a cognitively-inspired knowledge representation and reasoning system aimed at extending the capabilities of artificial systems in conceptual categorization tasks. It combines different sorts of common-sense categorization (prototypical and exemplars-based categorization) with standard monotonic categorization procedures. These different types of inferential procedures are reconciled according to the tenets coming from the dual process theory of reasoning. On the other hand, from a representational perspective, the system relies on the hypothesis of conceptual (...)
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  25. 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 natural but (...)
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  26. The False Dichotomy between Causal Realization and Semantic Computation.Marcin Miłkowski - 2017 - Hybris. Internetowy Magazyn Filozoficzny 38:1-21.
    In this paper, I show how semantic factors constrain the understanding of the computational phenomena to be explained so that they help build better mechanistic models. In particular, understanding what cognitive systems may refer to is important in building better models of cognitive processes. For that purpose, a recent study of some phenomena in rats that are capable of ‘entertaining’ future paths (Pfeiffer and Foster 2013) is analyzed. The case shows that the mechanistic account of physical computation may be complemented (...)
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  27. Critics of Computationalism and semantic aspects of phenomenal consciousness.Baryshnikov Pavel - 2017 - Philosphical Probllems of IT and Cyberspace 12 (2):14-30.
    This article focuses on the methodological basis for the criticism of the computationalism and “computer metaphor” in the philosophy of cognitive sciences. We suppose that the computational paradigm is the direct consequence of the theoretical confusion of phenomenal and cognitive kinds of experience. Cognitive processes, considered as the forms of computational description, are available for computer modelling. That implies the strong position of the computer metaphor in the neuroscience. In our opinion the key problem is the vague ontological nature of (...)
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  28. Ontologies, Disorders and Prototypes.Cristina Amoretti, Marcello Frixione, Antonio Lieto & Greta Adamo - 2016 - In Cristina Amoretti, Marcello Frixione, Antonio Lieto & Greta Adamo (eds.), Proceedings of IACAP 2016.
    As it emerged from philosophical analyses and cognitive research, most concepts exhibit typicality effects, and resist to the efforts of defining them in terms of necessary and sufficient conditions. This holds also in the case of many medical concepts. This is a problem for the design of computer science ontologies, since knowledge representation formalisms commonly adopted in this field (such as, in the first place, the Web Ontology Language - OWL) do not allow for the representation of concepts in terms (...)
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  29. Autômatos, Androides e Bergson ou A percepção e a Extensão em seres artificiais da Ficção: Um olhar Bergsoniano.Sandro Rinaldi Feliciano - 2016 - Dissertation, Universidade Federal Do Abc
    Androides são "autômatos com forma humana" . Enquanto robôs são "aparelhos automáticos capazes de manipular objetos ou executar operações segundo um programa". Assim podemos dizer que um androide pode ser considerado um robô, mas nem todo robô é um androide. Devido à diversidade de gêneros, foi criado o termo ginóide, separando-se assim os androides de aparência masculina (andros) da feminina (ginos). A propagação destes se deu à ficção cientifica, em livros de Isaac Asimov, em seriados para televisão como Jornada nas (...)
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  30. Minds, Models and Milieux: Commemorating the Centennial of the Birth of Herbert Simon.Roger Frantz & Leslie Marsh (eds.) - 2016 - Palgrave-Macmillan.
    This book is a collection of specially commissioned chapters from philosophers, economists, political and behavioral economists, cognitive and organizational psychologists, computer scientists, sociologists and permutations thereof as befits the polymathic subject of this book – Herbert Simon.
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  31. Subjective Probability as Sampling Propensity.Thomas Icard - 2016 - Review of Philosophy and Psychology 7 (4):863-903.
    Subjective probability plays an increasingly important role in many fields concerned with human cognition and behavior. Yet there have been significant criticisms of the idea that probabilities could actually be represented in the mind. This paper presents and elaborates a view of subjective probability as a kind of sampling propensity associated with internally represented generative models. The resulting view answers to some of the most well known criticisms of subjective probability, and is also supported by empirical work in neuroscience and (...)
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  32. Embodied Functionalism and Inner Complexity: Simon’s 21st-Century Mind.Robert D. Rupert - 2016 - In Roger Frantz & Leslie Marsh (eds.), Minds, Models and Milieux: Commemorating the Centennial of the Birth of Herbert Simon. Palgrave-Macmillan. pp. 7–33.
    This chapter argues that Simon anticipated what has emerged as the consensus view about human cognition: embodied functionalism. According to embodied functionalism, cognitive processes appear at a distinctively cognitive level; types of cognitive processes (such as proving a theorem) are not identical to kinds of neural processes, because the former can take various physical forms in various individual thinkers. Nevertheless, the distinctive characteristics of such processes — their causal structures — are determined by fine-grained properties shared by various, often especially (...)
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  33. Objective Computation Versus Subjective Computation.Nir Fresco - 2015 - Erkenntnis 80 (5):1031-1053.
    The question ‘What is computation?’ might seem a trivial one to many, but this is far from being in consensus in philosophy of mind, cognitive science and even in physics. The lack of consensus leads to some interesting, yet contentious, claims, such as that cognition or even the universe is computational. Some have argued, though, that computation is a subjective phenomenon: whether or not a physical system is computational, and if so, which computation it performs, is entirely a matter of (...)
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  34. Some Epistemological Problems with the Knowledge Level in Cognitive Architectures.Antonio Lieto - 2015 - In Proceedings of AISC 2015, 12th Italian Conference on Cognitive Science, Genoa, 10-12 December 2015, Italy. NeaScience.
    This article addresses an open problem in the area of cognitive systems and architectures: namely the problem of handling (in terms of processing and reasoning capabilities) complex knowledge structures that can be at least plausibly comparable, both in terms of size and of typology of the encoded information, to the knowledge that humans process daily for executing everyday activities. Handling a huge amount of knowledge, and selectively retrieve it according to the needs emerging in different situational scenarios, is an important (...)
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  35. A framework for the first‑person internal sensation of visual perception in mammals and a comparable circuitry for olfactory perception in Drosophila.Kunjumon Vadakkan - 2015 - Springerplus 4 (833):1-23.
    Perception is a first-person internal sensation induced within the nervous system at the time of arrival of sensory stimuli from objects in the environment. Lack of access to the first-person properties has limited viewing perception as an emergent property and it is currently being studied using third-person observed findings from various levels. One feasible approach to understand its mechanism is to build a hypothesis for the specific conditions and required circuit features of the nodal points where the mechanistic operation of (...)
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  36. A Computational Framework for Concept Representation in Cognitive Systems and Architectures: Concepts as Heterogeneous Proxytypes.Antonio Lieto - 2014 - Proceedings of 5th International Conference on Biologically Inspired Cognitive Architectures, Boston, MIT, Pocedia Computer Science, Elsevier:1-9.
    In this paper a possible general framework for the representation of concepts in cognitive artificial systems and cognitive architectures is proposed. The framework is inspired by the so called proxytype theory of concepts and combines it with the heterogeneity approach to concept representations, according to which concepts do not constitute a unitary phenomenon. The contribution of the paper is twofold: on one hand, it aims at providing a novel theoretical hypothesis for the debate about concepts in cognitive sciences by providing (...)
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  37. The embodied embedded character of system 1 processing.Samuel Bellini-Leite - 2013 - Mens Sana Monographs 11 (1):239-252.
    In the last thirty years, a relatively large group of cognitive scientists have begun characterising the mind in terms of two distinct, relatively autonomous systems. To account for paradoxes in empirical results of studies mainly on reasoning, Dual Process Theories were developed. Such Dual Process Theories generally agree that System 1 is rapid, automatic, parallel, and heuristic-based and System 2 is slow, capacity-demanding, sequential, and related to consciousness. While System 2 can still be decently understood from a traditional cognitivist approach, (...)
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  38. Dealing with Concepts: from Cognitive Psychology to Knowledge Representation.Marcello Frixione & Antonio Lieto - 2013 - Frontiers of Psychological and Behevioural Science 2 (3):96-106.
    Concept representation is still an open problem in the field of ontology engineering and, more generally, of knowledge representation. In particular, the issue of representing “non classical” concepts, i.e. concepts that cannot be defined in terms of necessary and sufficient conditions, remains unresolved. In this paper we review empirical evidence from cognitive psychology, according to which concept representation is not a unitary phenomenon. On this basis, we sketch some proposals for concept representation, taking into account suggestions from psychological research. In (...)
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  39. Artificial Intelligence and Cognition. Proceedings of the First International Workshop AIC 2013.Antonio Lieto & Marco Cruciani (eds.) - 2013 - CEUR Workshop Proceedings.
  40. Meinongian Semantics and Artificial Intelligence.William J. Rapaport - 2013 - Humana Mente 6 (25):25-52.
    This essay describes computational semantic networks for a philosophical audience and surveys several approaches to semantic-network semantics. In particular, propositional semantic networks are discussed; it is argued that only a fully intensional, Meinongian semantics is appropriate for them; and several Meinongian systems are presented.
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  41. Ethical Aspects of Computational Neuroscience.Tyler D. Bancroft - 2012 - Neuroethics 6 (2):415-418.
    Recent research in computational neuroscience has demonstrated that we now possess the ability to simulate neural systems in significant detail and on a large scale. Simulations on the scale of a human brain have recently been reported. The ability to simulate entire brains (or significant portions thereof) would be a revolutionary scientific advance, with substantial benefits for brain science. However, the prospect of whole-brain simulation comes with a set of new and unique ethical questions. In the present paper, we briefly (...)
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  42. Vagueness Intuitions and the Mobility of Cognitive Sortals.Bert Baumgaertner - 2012 - Minds and Machines 22 (3):213-234.
    One feature of vague predicates is that, as far as appearances go, they lack sharp application boundaries. I argue that we would not be able to locate boundaries even if vague predicates had sharp boundaries. I do so by developing an idealized cognitive model of a categorization faculty which has mobile and dynamic sortals (`classes', `concepts' or `categories') and formally prove that the degree of precision with which boundaries of such sortals can be located is inversely constrained by their flexibility. (...)
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  43. 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 rather (...)
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  44. The (lack of) mental life of some machines.Tomer Fekete & Shimon Edelman - 2012 - In Shimon Edelman, Tomer Fekete & Neta Zach (eds.), Being in Time: Dynamical Models of Phenomenal Experience. John Benjamins.. pp. 88--95.
    The proponents of machine consciousness predicate the mental life of a machine, if any, exclusively on its formal, organizational structure, rather than on its physical composition. Given that matter is organized on a range of levels in time and space, this generic stance must be further constrained by a principled choice of levels on which the posited structure is supposed to reside. Indeed, not only must the formal structure fit well the physical system that realizes it, but it must do (...)
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  45. Representing Concepts in Formal Ontologies: Compositionality vs. Typicality Effects".Marcello Frixione & Antonio Lieto - 2012 - Logic and Logical Philosophy 21 (4):391-414.
    The problem of concept representation is relevant for many sub-fields of cognitive research, including psychology and philosophy, as well as artificial intelligence. In particular, in recent years it has received a great deal of attention within the field of knowledge representation, due to its relevance for both knowledge engineering as well as ontology-based technologies. However, the notion of a concept itself turns out to be highly disputed and problematic. In our opinion, one of the causes of this state of affairs (...)
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  46. Implications of a logical paradox for computer-dispensed justice reconsidered: some key differences between minds and machines.Joseph S. Fulda - 2012 - Artificial Intelligence and Law 20 (3):321-333.
    We argued [Since this argument appeared in other journals, I am reprising it here, almost verbatim.] (Fulda in J Law Info Sci 2:230–232, 1991/AI & Soc 8(4):357–359, 1994) that the paradox of the preface suggests a reason why machines cannot, will not, and should not be allowed to judge criminal cases. The argument merely shows that they cannot now and will not soon or easily be so allowed. The author, in fact, now believes that when—and only when—they are ready they (...)
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  47. Empirically grounded claims about consciousness in computers.David Gamez - 2012 - International Journal of Machine Consciousness 4 (2):421-438.
    Research is starting to identify correlations between consciousness and some of the spatiotemporal patterns in the physical brain. For theoretical and practical reasons, the results of experiments on the correlates of consciousness have ambiguous interpretations. At any point in time a number of hypotheses co-exist about and the correlates of consciousness in the brain, which are all compatible with the current experimental results. This paper argues that consciousness should be attributed to any system that exhibits spatiotemporal physical patterns that match (...)
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  48. Origins of Objectivity.Robert W. Lurz - 2012 - Philosophical Psychology 25 (5):775-781.
    Philosophical Psychology, Volume 0, Issue 0, Page 1-7, Ahead of Print.
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  49. You Can't Eat Causal Cake with an Abstract Fork: An Argument Against Computational Theories of Consciousness.Matthew Stuart Piper - 2012 - Journal of Consciousness Studies 19 (11-12):154-90.
    Two of the most important concepts in contemporary philosophy of mind are computation and consciousness. This paper explores whether there is a strong relationship between these concepts in the following sense: is a computational theory of consciousness possible? That is, is the right kind of computation sufficient for the instantiation of consciousness. In this paper, I argue that the abstract nature of computational processes precludes computations from instantiating the concrete properties constitutive of consciousness. If this is correct, then not only (...)
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  50. An appreciation of John Pollock's work on the computational study of argument.Henry Prakken & John Horty - 2012 - Argument and Computation 3 (1):1 - 19.
    John Pollock (1940?2009) was an influential American philosopher who made important contributions to various fields, including epistemology and cognitive science. In the last 25 years of his life, he also contributed to the computational study of defeasible reasoning and practical cognition in artificial intelligence. He developed one of the first formal systems for argumentation-based inference and he put many issues on the research agenda that are still relevant for the argumentation community today. This paper presents an appreciation of Pollock's work (...)
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