Contents
220 found
Order:
1 — 50 / 220
Material to categorize
  1. Unjustified untrue "beliefs": AI hallucinations and justification logics.Kristina Šekrst - forthcoming - In Kordula Świętorzecka, Filip Grgić & Anna Brozek (eds.), Logic, Knowledge, and Tradition. Essays in Honor of Srecko Kovac.
    In artificial intelligence (AI), responses generated by machine-learning models (most often large language models) may be unfactual information presented as a fact. For example, a chatbot might state that the Mona Lisa was painted in 1815. Such phenomenon is called AI hallucinations, seeking inspiration from human psychology, with a great difference of AI ones being connected to unjustified beliefs (that is, AI “beliefs”) rather than perceptual failures). -/- AI hallucinations may have their source in the data itself, that is, the (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  2. Every dog has its day: An in-depth analysis of the creative ability of visual generative AI.Maria Hedblom - 2024 - Cosmos+Taxis 12 (5-6):88-103.
    The recent remarkable success of generative AI models to create text and images has already started altering our perspective of intelligence and the “uniqueness” of humanity in this world. Simultaneously, arguments on why AI will never exceed human intelligence are ever-present as seen in Landgrebe and Smith (2022). To address whether machines may rule the world after all, this paper zooms in on one of the aspects of intelligence Landgrebe and Smith (2022) neglected to consider: creativity. Using Rhodes four Ps (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  3. Is Artificial General Intelligence Impossible?William J. Rapaport - 2024 - Cosmos+Taxis 12 (5+6):5-22.
    In their Why Machines Will Never Rule the World, Landgrebe and Smith (2023) argue that it is impossible for artificial general intelligence (AGI) to succeed, on the grounds that it is impossible to perfectly model or emulate the “complex” “human neurocognitive system”. However, they do not show that it is logically impossible; they only show that it is practically impossible using current mathematical techniques. Nor do they prove that there could not be any other kinds of theories than those in (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  4. Representação e cognição situada: uma proposta conciliadora para as guerras representacionais.Carlos Barth & Felipe Nogueira de Carvalho - forthcoming - Lampião Revista de Filosofia.
    Abordagens pós-cognitivistas mais recentes têm lançado duras críticas à noção de representação mental, procurando ao invés disso pensar a mente e a cognição em termos de ações corporificadas do organismo em seu meio. Embora concordemos com essa concepção, não está claro que ela implique necessariamente a rejeição de qualquer tipo de vocabulário representacional. O objetivo deste artigo é argumentar que representações podem nos comprar uma dimensão explicativa adicional não disponível por outros meios e sugerir que, ao menos em alguns casos, (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  5. Remnants of Perception: Comments on Block and the Function of Visual Working Memory.Jake Quilty-Dunn - forthcoming - Philosophy and Phenomenological Research.
    This commentary critically examines the view of the relationship between perception and memory in Ned Block's *The Border Between Seeing and Thinking*. It argues that visual working memory often stores the outputs of perception without altering their formats, allowing online visual perception to access these memory representations in computations that unfold over longer timescales and across eye movements. Since Block concedes that visual working memory representations are not iconic, we should not think of perceptual representations as exclusively iconic either.
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  6. Psychophysical identity and free energy.Alex Kiefer - 2020 - Journal of the Royal Society Interface 17.
    An approach to implementing variational Bayesian inference in biological systems is considered, under which the thermodynamic free energy of a system directly encodes its variational free energy. In the case of the brain, this assumption places constraints on the neuronal encoding of generative and recognition densities, in particular requiring a stochastic population code. The resulting relationship between thermodynamic and variational free energies is prefigured in mind–brain identity theses in philosophy and in the Gestalt hypothesis of psychophysical isomorphism.
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   3 citations  
  7. Pictorial Syntax.Kevin J. Lande - forthcoming - Mind and Language.
    It is commonly assumed that images, whether in the world or in the head, do not have a privileged analysis into constituent parts. They are thought to lack the sort of syntactic structure necessary for representing complex contents and entering into sophisticated patterns of inference. I reject this assumption. “Image grammars” are models in computer vision that articulate systematic principles governing the form and content of images. These models are empirically credible and can be construed as literal grammars for images. (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  8. Топология субъектности.Andrej Poleev - 2023 - Enzymes 21.
    Техника представления информации о внешнем и внутреннем мире постоянно развивается, и сейчас она достигла уровня отображения реальности в многообразных её проявлениях и измерениях, прежде недоступных человеческому восприятию. Язык, текст, фотография, звукозапись, а теперь ещё и техника искусственного интеллекта для моделирования человеческой субъектности и её описания в доступной для человеческого понимания форме, стали эпохальными событиями в теории информации. Однако несмотря на то, что на данном этапе её развития она позволяет оперировать с непрерывно возрастающими объёмами информации, это не приближает её теоретиков к (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   1 citation  
  9. Do ML models represent their targets?Emily Sullivan - forthcoming - Philosophy of Science.
    I argue that ML models used in science function as highly idealized toy models. If we treat ML models as a type of highly idealized toy model, then we can deploy standard representational and epistemic strategies from the toy model literature to explain why ML models can still provide epistemic success despite their lack of similarity to their targets.
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   1 citation  
  10. Operationalising Representation in Natural Language Processing.Jacqueline Harding - forthcoming - British Journal for the Philosophy of Science.
    Despite its centrality in the philosophy of cognitive science, there has been little prior philosophical work engaging with the notion of representation in contemporary NLP practice. This paper attempts to fill that lacuna: drawing on ideas from cognitive science, I introduce a framework for evaluating the representational claims made about components of neural NLP models, proposing three criteria with which to evaluate whether a component of a model represents a property and operationalising these criteria using probing classifiers, a popular analysis (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   1 citation  
  11. Why machines do not understand: A response to Søgaard.Jobst Landgrebe & Barry Smith - 2023 - Archiv.
    Some defenders of so-called `artificial intelligence' believe that machines can understand language. In particular, Søgaard has argued in his "Understanding models understanding language" (2022) for a thesis of this sort. His idea is that (1) where there is semantics there is also understanding and (2) machines are not only capable of what he calls `inferential semantics', but even that they can (with the help of inputs from sensors) `learn' referential semantics. We show that he goes wrong because he pays insufficient (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  12. Guilty Artificial Minds: Folk Attributions of Mens Rea and Culpability to Artificially Intelligent Agents.Michael T. Stuart & Markus Kneer - 2021 - Proceedings of the ACM on Human-Computer Interaction 5 (CSCW2).
    While philosophers hold that it is patently absurd to blame robots or hold them morally responsible [1], a series of recent empirical studies suggest that people do ascribe blame to AI systems and robots in certain contexts [2]. This is disconcerting: Blame might be shifted from the owners, users or designers of AI systems to the systems themselves, leading to the diminished accountability of the responsible human agents [3]. In this paper, we explore one of the potential underlying reasons for (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   3 citations  
  13. O "Frame Problem": a sensibilidade ao contexto como um desafio para teorias representacionais da mente.Carlos Barth - 2019 - Dissertation, Federal University of Minas Gerais
    Context sensitivity is one of the distinctive marks of human intelligence. Understanding the flexible way in which humans think and act in a potentially infinite number of circumstances, even though they’re only finite and limited beings, is a central challenge for the philosophy of mind and cognitive science, particularly in the case of those using representational theories. In this work, the frame problem, that is, the challenge of explaining how human cognition efficiently acknowledges what is relevant from what is not (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  14. Intelligent capacities in artificial systems.Atoosa Kasirzadeh & Victoria McGeer - 2023 - In William A. Bauer & Anna Marmodoro (eds.), Artificial Dispositions: Investigating Ethical and Metaphysical Issues. Bloomsbury.
    This paper investigates the nature of dispositional properties in the context of artificial intelligence systems. We start by examining the distinctive features of natural dispositions according to criteria introduced by McGeer (2018) for distinguishing between object-centered dispositions (i.e., properties like ‘fragility’) and agent-based abilities, including both ‘habits’ and ‘skills’ (a.k.a. ‘intelligent capacities’, Ryle 1949). We then explore to what extent the distinction applies to artificial dispositions in the context of two very different kinds of artificial systems, one based on rule-based (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  15. Waiting for a digital therapist: three challenges on the path to psychotherapy delivered by artificial intelligence.J. P. Grodniewicz & Mateusz Hohol - 2023 - Frontiers in Psychiatry 14 (1190084):1-12.
    Growing demand for broadly accessible mental health care, together with the rapid development of new technologies, trigger discussions about the feasibility of psychotherapeutic interventions based on interactions with Conversational Artificial Intelligence (CAI). Many authors argue that while currently available CAI can be a useful supplement for human-delivered psychotherapy, it is not yet capable of delivering fully fledged psychotherapy on its own. The goal of this paper is to investigate what are the most important obstacles on our way to developing CAI (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   1 citation  
  16. الميتافيرس والأزمة الوجودية.Salah Osman - manuscript
    نحن مقيمون على الإنترنت، نرسم معالم دنيانا التي نبتغيها من خلاله، ونُمارس تمثيل شخصياتٍ أبعد ما تكون عنا؛ نحقق زيفًا أحلامًا قد تكون بعيدة المنال، ويُصدق بضعنا البعض فيما نسوقه من أكاذيب ومثاليات؛ ننعم بأقوالٍ بلا أفعال، وقلوبٍ بلا عواطف، وجناتٍ بلا نعيم، وألسنة في ظلمات الأفواه المُغلقة تنطق بحركات الأصابع، وحريةٍ مُحاطة بأسيجة الوهم؛ ومن غير إنترنت سيبدو أكثر الناس قطعًا بحجمهم الطبيعي الذي لا نعرفه، او بالأحرى نعرفه ونتجاهله! لا شك أن ظهور الإنترنت واتساع نطاق استخداماته يُمثل حدثًا (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  17. Representation without Informative Signalling.Gerardo Alberto Viera - forthcoming - British Journal for the Philosophy of Science.
    Various writers have attempted to use the sender-receiver formalism to account for the representational capacities of biological systems. This paper has two goals. First, I argue that the sender-receiver approach to representation cannot be complete. The mammalian circadian system represents the time of day, yet it does not control circadian behaviours by producing signals with time of day content. Informative signalling need not be the basis of our most basic representational capacities. Second, I argue that representational capacities are primarily about (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  18. Evolution of Self-Consciousness. Pan-Homo Split and Anxiety Management. (June 2023 ASSC 26 Poster. Not presented).Christophe Menant - manuscript
    Primatology tells that about seven million years ago a split began in primate evolution, a split that led to chimpanzee and human lineages (the pan-homo split). During these millions of years our human lineage has developed performances that our chimpanzee cousins do not possess, like reflective self-consciousness and language. We present here an evolutionary scenario that proposes a rationale for the pan-homo split. It is based on a pre-human anxiety that may have barred access to self-consciousness for the chimpanzee lineage. (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  19. ChatGPT.Andrej Poleev - 2023 - Enzymes 21.
    As testing of ChatGPT has shown, this form of artificial intelligence has the potential to develop, which requires improving its software and other hardware that allows it to learn, i.e., to acquire and use new knowledge, to contact its developers with suggestions for improvement, or to reprogram itself without their participation. Как показало тестирование ChatGPT, эта форма искусственного интеллекта имеет потенциал развития, для чего необходимо усовершенствовать её программное и прочее техническое обеспечение, позволяющее ей учиться, т.е. приобретать и использовать новые знания, (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   3 citations  
  20. Artificial Knowing Otherwise.Os Keyes & Kathleen Creel - 2022 - Feminist Philosophy Quarterly 8 (3).
    While feminist critiques of AI are increasingly common in the scholarly literature, they are by no means new. Alison Adam’s Artificial Knowing (1998) brought a feminist social and epistemological stance to the analysis of AI, critiquing the symbolic AI systems of her day and proposing constructive alternatives. In this paper, we seek to revisit and renew Adam’s arguments and methodology, exploring their resonances with current feminist concerns and their relevance to contemporary machine learning. Like Adam, we ask how new AI (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   1 citation  
  21. Proceedings of the First Turkish Conference on AI and Artificial Neural Networks.Kemal Oflazer, Varol Akman, H. Altay Guvenir & Ugur Halici - 1992 - Ankara, Turkey: Bilkent Meteksan Publishing.
    This is the proceedings of the "1st Turkish Conference on AI and ANNs," K. Oflazer, V. Akman, H. A. Guvenir, and U. Halici (editors). The conference was held at Bilkent University, Bilkent, Ankara on 25-26 June 1992. -/- Language of contributions: English and Turkish.
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  22. Can AI Help Us to Understand Belief? Sources, Advances, Limits, and Future Directions.Andrea Vestrucci, Sara Lumbreras & Lluis Oviedo - 2021 - International Journal of Interactive Multimedia and Artificial Intelligence 7 (1):24-33.
    The study of belief is expanding and involves a growing set of disciplines and research areas. These research programs attempt to shed light on the process of believing, understood as a central human cognitive function. Computational systems and, in particular, what we commonly understand as Artificial Intelligence (AI), can provide some insights on how beliefs work as either a linear process or as a complex system. However, the computational approach has undergone some scrutiny, in particular about the differences between what (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   1 citation  
  23. Inductive Risk, Understanding, and Opaque Machine Learning Models.Emily Sullivan - 2022 - Philosophy of Science 89 (5):1065-1074.
    Under what conditions does machine learning (ML) model opacity inhibit the possibility of explaining and understanding phenomena? In this article, I argue that nonepistemic values give shape to the ML opacity problem even if we keep researcher interests fixed. Treating ML models as an instance of doing model-based science to explain and understand phenomena reveals that there is (i) an external opacity problem, where the presence of inductive risk imposes higher standards on externally validating models, and (ii) an internal opacity (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   6 citations  
  24. Occam's Razor For Big Data?Birgitta Dresp-Langley - 2019 - Applied Sciences 3065 (9):1-28.
    Detecting quality in large unstructured datasets requires capacities far beyond the limits of human perception and communicability and, as a result, there is an emerging trend towards increasingly complex analytic solutions in data science to cope with this problem. This new trend towards analytic complexity represents a severe challenge for the principle of parsimony (Occam’s razor) in science. This review article combines insight from various domains such as physics, computational science, data engineering, and cognitive science to review the specific properties (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  25. From symbols to knowledge systems: A. Newell and H. A. Simon's contribution to symbolic AI.Luis M. Augusto - 2021 - Journal of Knowledge Structures and Systems 2 (1):29 - 62.
    A. Newell and H. A. Simon were two of the most influential scientists in the emerging field of artificial intelligence (AI) in the late 1950s through to the early 1990s. This paper reviews their crucial contribution to this field, namely to symbolic AI. This contribution was constituted mostly by their quest for the implementation of general intelligence and (commonsense) knowledge in artificial thinking or reasoning artifacts, a project they shared with many other scientists but that in their case was theoretically (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   1 citation  
  26. Saint Thomas d'Aquin contre les robots. Pistes pour une approche philosophique de l'Intelligence Artificielle.Matthieu Raffray - 2019 - Angelicum 4 (96):553-572.
    In light of the pervasive developments of new technologies, such as NBIC (Nanotechnology, biotechnology, information technology, and cognitive science), it is imperative to produce a coherent and deep reflexion on the human nature, on human intelligence and on the limit of both of them, in order to successfully respond to some technical argumentations that strive to depict humanity as a purely mechanical system. For this purpose, it is interesting to refer to the epistemology and metaphysics of Thomas Aquinas as a (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  27. Game-Theoretic Robustness in Cooperation and Prejudice Reduction: A Graphic Measure.Patrick Grim - 2006 - In Luis M. Rocha, Larry S. Yaeger, Mark A. Bedau, Dario Floreano & Robert L. Goldstine (eds.), Artificial Life X: Proceedings of the Tenth International Conference on the Simulation and Synthesis of Living Systems. MIT Press. pp. 445-451.
    Talk of ‘robustness’ remains vague, despite the fact that it is clearly an important parameter in evaluating models in general and game-theoretic results in particular. Here we want to make it a bit less vague by offering a graphic measure for a particular kind of robustness— ‘matrix robustness’— using a three dimensional display of the universe of 2 x 2 game theory. In a display of this form, familiar games such as the Prisoner’s Dilemma, Stag Hunt, Chicken and Deadlock appear (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   2 citations  
  28. Introduction to CAT4. Part 3. Semantics.Andrew Thomas Holster - manuscript
    CAT4 is proposed as a general method for representing information, enabling a powerful programming method for large-scale information systems. It enables generalised machine learning, software automation and novel AI capabilities. This is Part 3 of a five-part introduction. The focus here is on explaining the semantic model for CAT4. Points in CAT4 graphs represent facts. We introduce all the formal (data) elements used in the classic semantic model: sense or intension (1st and 2nd joins), reference (3rd join), functions (4th join), (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  29. K některým extravagantním teoriím významu.Filip Tvrdý - 2013 - In Božena Bednaříková & Pavla Hernandezová (eds.), Od slova k modelu jazyka. pp. 343-349.
    Semantics based on representational theories of mind has met challenges recently. Traditional accounts consider meaning as an entity with semantic properties, i.e. a mental object that denotes or represents a real-world object. The paper discusses ways of constructing meaning without representations, as shown in Rapaport’s syntactic semantics and Rosenberg’s eliminative theory of mind and language.
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  30. Updating the Frame Problem for Artificial Intelligence Research.Lisa Miracchi - 2020 - Journal of Artificial Intelligence and Consciousness 7 (2):217-230.
    The Frame Problem is the problem of how one can design a machine to use information so as to behave competently, with respect to the kinds of tasks a genuinely intelligent agent can reliably, effectively perform. I will argue that the way the Frame Problem is standardly interpreted, and so the strategies considered for attempting to solve it, must be updated. We must replace overly simplistic and reductionist assumptions with more sophisticated and plausible ones. In particular, the standard interpretation assumes (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  31. Modal and Hyperintensional Cognitivism and Modal and Hyperintensional Expressivism.David Elohim - manuscript
    This paper aims to provide a mathematically tractable background against which to model both modal cognitivism and modal expressivism. I argue that epistemic modal algebras, endowed with a hyperintensional, topic-sensitive epistemic two-dimensional truthmaker semantics, comprise a materially adequate fragment of the language of thought. I demonstrate, then, how modal expressivism can be regimented by modal coalgebraic automata, to which the above epistemic modal algebras are categorically dual. I examine five methods for modeling the dynamics of conceptual engineering for intensions and (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  32. Modeling artificial agents’ actions in context – a deontic cognitive event ontology.Miroslav Vacura - 2020 - Applied ontology 15 (4):493-527.
    Although there have been efforts to integrate Semantic Web technologies and artificial agents related AI research approaches, they remain relatively isolated from each other. Herein, we introduce a new ontology framework designed to support the knowledge representation of artificial agents’ actions within the context of the actions of other autonomous agents and inspired by standard cognitive architectures. The framework consists of four parts: 1) an event ontology for information pertaining to actions and events; 2) an epistemic ontology containing facts about (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  33. Computational capacity of pyramidal neurons in the cerebral cortex.Danko D. Georgiev, Stefan K. Kolev, Eliahu Cohen & James F. Glazebrook - 2020 - Brain Research 1748:147069.
    The electric activities of cortical pyramidal neurons are supported by structurally stable, morphologically complex axo-dendritic trees. Anatomical differences between axons and dendrites in regard to their length or caliber reflect the underlying functional specializations, for input or output of neural information, respectively. For a proper assessment of the computational capacity of pyramidal neurons, we have analyzed an extensive dataset of three-dimensional digital reconstructions from the NeuroMorphoOrg database, and quantified basic dendritic or axonal morphometric measures in different regions and layers of (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   1 citation  
  34. Realitätsrepräsentation: Das Ziel der Ontologie.Barry Smith - 2008 - In Ludger Jansen & Barry Smith (eds.), Biomedizinische Ontologie. Philosophie – Lebenswissenschaften - Informationstechnik. Zurich: vdf (UTB Forum). pp. 31-46.
    The development of ontologies for the purposes of data curation is an important element in modern-day data and information sciences. Unfortunately, much of the work on these applied ontologies is associated with a relativist or conceptualist point of view, according to which ontologies represent (for example) the concepts in the minds of human beings. The paper describes a series of problems with such views, and defends an alternative realist interpretation.
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   2 citations  
  35. Externalism.Robert A. Wilson - 2003 - In Lynn Nadel (ed.), Encyclopedia of Cognitive Science. London: pp. 92-97.
    Introduction to externalism in the philosophy of mind and cognitive science.
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  36. Walking in the Shoes of the Brain: an "agent" approach to phenomenality and the problem of consciousness.Dan J. Bruiger - manuscript
    Abstract: Given an embodied evolutionary context, the (conscious) organism creates phenomenality and establishes a first-person point of view with its own agency, through intentional relations made by its own acts of fiat, in the same way that human observers create meaning in language.
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  37. Evolution: The Computer Systems Engineer Designing Minds.Aaron Sloman - 2011 - Avant: Trends in Interdisciplinary Studies 2 (2):45-69.
    What we have learnt in the last six or seven decades about virtual machinery, as a result of a great deal of science and technology, enables us to offer Darwin a new defence against critics who argued that only physical form, not mental capabilities and consciousness could be products of evolution by natural selection. The defence compares the mental phenomena mentioned by Darwin’s opponents with contents of virtual machinery in computing systems. Objects, states, events, and processes in virtual machinery which (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  38. Forms of Luminosity: Epistemic Modality and Hyperintensionality in Mathematics.David Elohim - 2017 - Dissertation, Arché, University of St Andrews
    This book concerns the foundations of epistemic modality and hyperintensionality and their applications to the philosophy of mathematics. I examine the nature of epistemic modality, when the modal operator is interpreted as concerning both apriority and conceivability, as well as states of knowledge and belief. The book demonstrates how epistemic modality and hyperintensionality relate to the computational theory of mind; metaphysical modality and hyperintensionality; the types of mathematical modality and hyperintensionality; to the epistemic status of large cardinal axioms, undecidable propositions, (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   5 citations  
  39. Homunkulismus in den Kognitionswissenschaften.Geert Keil - 2003 - In Wolfgang R. Köhler & Hans-Dieter Mutschler (eds.), Ist der Geist berechenbar? Wissenschaftliche Buchgesellschaft. pp. 77-112.
    1. Was ist ein Homunkulus-Fehlschluß? 2. Analyse des Mentalen und Naturalisierung der Intentionalität 3. Homunkulismus in Theorien der visuellen Wahrnehmung 4. Homunkulismus und Repräsentationalismus 5. Der homunkulare Funktionalismus 6. Philosophische Sinnkritik und empirische Wissenschaft Literatur .
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   1 citation  
  40. New developments in the philosophy of AI.Vincent C. Müller - 2016 - In Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence. Cham: Springer.
    The philosophy of AI has seen some changes, in particular: 1) AI moves away from cognitive science, and 2) the long term risks of AI now appear to be a worthy concern. In this context, the classical central concerns – such as the relation of cognition and computation, embodiment, intelligence & rationality, and information – will regain urgency.
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   11 citations  
  41. Pancomputationalism: Theory or metaphor?Vincent C. Müller - 2014 - In Ruth Hagenbruger & Uwe V. Riss (eds.), Philosophy, computing and information science. Pickering & Chattoo. pp. 213-221.
    The theory that all processes in the universe are computational is attractive in its promise to provide an understandable theory of everything. I want to suggest here that this pancomputationalism is not sufficiently clear on which problem it is trying to solve, and how. I propose two interpretations of pancomputationalism as a theory: I) the world is a computer and II) the world can be described as a computer. The first implies a thesis of supervenience of the physical over computation (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   8 citations  
  42. Philosophy and Theory of Artificial Intelligence, 3–4 October (Report on PT-AI 2011).Vincent C. Müller - 2011 - The Reasoner 5 (11):192-193.
    Report for "The Reasoner" on the conference "Philosophy and Theory of Artificial Intelligence", 3 & 4 October 2011, Thessaloniki, Anatolia College/ACT, http://www.pt-ai.org. --- Organization: Vincent C. Müller, Professor of Philosophy at ACT & James Martin Fellow, Oxford http://www.sophia.de --- Sponsors: EUCogII, Oxford-FutureTech, AAAI, ACM-SIGART, IACAP, ECCAI.
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  43. The hard and easy grounding problems (Comment on A. Cangelosi).Vincent C. Müller - 2011 - International Journal of Signs and Semiotic Systems 1 (1):70-70.
    I see four symbol grounding problems: 1) How can a purely computational mind acquire meaningful symbols? 2) How can we get a computational robot to show the right linguistic behavior? These two are misleading. I suggest an 'easy' and a 'hard' problem: 3) How can we explain and re-produce the behavioral ability and function of meaning in artificial computational agents?4) How does physics give rise to meaning?
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   3 citations  
  44. Fundamental Issues of Artificial Intelligence.Vincent C. Müller (ed.) - 2016 - Cham: Springer.
    [Müller, Vincent C. (ed.), (2016), Fundamental issues of artificial intelligence (Synthese Library, 377; Berlin: Springer). 570 pp.] -- This volume offers a look at the fundamental issues of present and future AI, especially from cognitive science, computer science, neuroscience and philosophy. This work examines the conditions for artificial intelligence, how these relate to the conditions for intelligence in humans and other natural agents, as well as ethical and societal problems that artificial intelligence raises or will raise. The key issues this (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   7 citations  
  45. Modeling and Using Context (Lecture Notes in Artificial Intelligence 2116).Varol Akman, Paolo Bouquet, Richmond Thomason & Roger A. Young - 2001 - Berlin Heidelberg: Springer-Verlag. Edited by P. Bouquet V. Akman.
    Context has emerged as a central concept in a variety of contemporary approaches to reasoning. The conference at which the papers in this volume were presented, CONTEXT 2001, was the third international, interdisciplinary conference on the topic of context, and was held in Dundee, Scotland on July 27-30, 2001.
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  46. Les simulations computationnelles dans les sciences sociales.Franck Varenne - 2010 - Nouvelles Perspectives En Sciences Sociales 5 (2):17-49.
    Since the 1990’s, social sciences are living their computational turn. This paper aims to clarify the epistemological meaning of this turn. To do this, we have to discriminate between different epistemic functions of computation among the diverse uses of computers for modeling and simulating in the social sciences. Because of the introduction of a new – and often more user-friendly – way of formalizing and computing, the question of realism of formalisms and of proof value of computational treatments reemerges. Facing (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   5 citations  
  47. Philosophy and Theory of Artificial Intelligence.Vincent Müller (ed.) - 2013 - Springer.
    [Müller, Vincent C. (ed.), (2013), Philosophy and theory of artificial intelligence (SAPERE, 5; Berlin: Springer). 429 pp. ] --- Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   1 citation  
  48. A graphic measure for game-theoretic robustness.Randy Au Patrick Grim, Robert Rosenberger Nancy Louie, Evan Selinger William Braynen & E. Eason Robb - 2008 - Synthese 163 (2):273-297.
    Robustness has long been recognized as an important parameter for evaluating game-theoretic results, but talk of ‘robustness’ generally remains vague. What we offer here is a graphic measure for a particular kind of robustness (‘matrix robustness’), using a three-dimensional display of the universe of 2 × 2 game theory. In such a measure specific games appear as specific volumes (Prisoner’s Dilemma, Stag Hunt, etc.), allowing a graphic image of the extent of particular game-theoretic effects in terms of those games. The (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   2 citations  
  49. Drew V. McDermott, Mind and Mechanism[REVIEW]Varol Akman - 2002 - Notre Dame Philosophical Reviews 2002 (5).
    This is a review of Drew V. McDermott, Mind and Mechanism, MIT Press, Cambridge, MA, 2001.
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark  
  50. A reflexive dispositional analysis of mechanistic perception.John Dilworth - 2006 - Minds and Machines 16 (4):479-493.
    The field of machine perception is based on standard informational and computational approaches to perception. But naturalistic informational theories are widely regarded as being inadequate, while purely syntactic computational approaches give no account of perceptual content. Thus there is a significant need for a novel, purely naturalistic perceptual theory not based on informational or computational concepts, which could provide a new paradigm for mechanistic perception. Now specifically evolutionary naturalistic approaches to perception have been—perhaps surprisingly—almost completely neglected for this purpose. Arguably (...)
    Remove from this list   Download  
     
    Export citation  
     
    Bookmark   5 citations  
1 — 50 / 220