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  1. In 30 Schritten zum Mond? Zukünftiger Fortschritt in der KI.Vincent C. Müller - 2018 - Medienkorrespondenz 20 (05.10.2018):5-15.
    Die Entwicklungen in der Künstlichen Intelligenz (KI) sind spannend. Aber wohin geht die Reise? Ich stelle eine Analyse vor, der zufolge exponentielles Wachstum von Rechengeschwindigkeit und Daten die entscheidenden Faktoren im bisherigen Fortschritt waren. Im Folgenden erläutere ich, unter welchen Annahmen dieses Wachstum auch weiterhin Fortschritt ermöglichen wird: 1) Intelligenz ist eindimensional und messbar, 2) Kognitionswissenschaft wird für KI nicht benötigt, 3) Berechnung (computation) ist hinreichend für Kognition, 4) Gegenwärtige Techniken und Architektur sind ausreichend skalierbar, 5) Technological Readiness Levels (TRL) (...)
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  2. Philosophy and Theory of Artificial Intelligence 2017.Vincent Müller (ed.) - 2017 - Berlin: Springer.
    This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI safety; (...)
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  3. Should Machines Be Tools or Tool-Users? Clarifying Motivations and Assumptions in the Quest for Superintelligence.Dan J. Bruiger - manuscript
    Much of the basic non-technical vocabulary of artificial intelligence is surprisingly ambiguous. Some key terms with unclear meanings include intelligence, embodiment, simulation, mind, consciousness, perception, value, goal, agent, knowledge, belief, optimality, friendliness, containment, machine and thinking. Much of this vocabulary is naively borrowed from the realm of conscious human experience to apply to a theoretical notion of “mind-in-general” based on computation. However, if there is indeed a threshold between mechanical tool and autonomous agent (and a tipping point for singularity), projecting (...)
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  4. Genes, Affect, and Reason: Why Autonomous Robot Intelligence Will Be Nothing Like Human Intelligence.Henry Moss - 2016 - Techné: Research in Philosophy and Technology 20 (1):1-15.
    Abstract: Many believe that, in addition to cognitive capacities, autonomous robots need something similar to affect. As in humans, affect, including specific emotions, would filter robot experience based on a set of goals, values, and interests. This narrows behavioral options and avoids combinatorial explosion or regress problems that challenge purely cognitive assessments in a continuously changing experiential field. Adding human-like affect to robots is not straightforward, however. Affect in organisms is an aspect of evolved biological systems, from the taxes of (...)
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  5. Future Progress in Artificial Intelligence: A Poll Among Experts.Vincent C. Müller & Nick Bostrom - 2014 - AI Matters 1 (1):9-11.
    [This is the short version of: Müller, Vincent C. and Bostrom, Nick (forthcoming 2016), ‘Future progress in artificial intelligence: A survey of expert opinion’, in Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence (Synthese Library 377; Berlin: Springer).] - - - In some quarters, there is intense concern about high–level machine intelligence and superintelligent AI coming up in a few dec- ades, bringing with it significant risks for human- ity; in other quarters, these issues are ignored or considered science (...)
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  6. Future Progress in Artificial Intelligence: A Survey of Expert Opinion.Vincent C. Müller & Nick Bostrom - 2016 - In Vincent Müller (ed.), Fundamental Issues of Artificial Intelligence. Springer. pp. 553-571.
    There is, in some quarters, concern about high–level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development, and how fast they see these developing. We thus (...)
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  7. Challenges for Artificial Cognitive Systems.Antoni Gomila & Vincent C. Müller - 2012 - Journal of Cognitive Science 13 (4):452-469.
    The declared goal of this paper is to fill this gap: “... cognitive systems research needs questions or challenges that define progress. The challenges are not (yet more) predictions of the future, but a guideline to what are the aims and what would constitute progress.” – the quotation being from the project description of EUCogII, the project for the European Network for Cognitive Systems within which this formulation of the ‘challenges’ was originally developed (http://www.eucognition.org). So, we stick out our neck (...)
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  8. 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.
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  9. How Do We Read a Dictionary (as Machines and as Humans)? Kinds of Information in Dictionaries Constructed and Reconstructed.Vincent C. Müller - 2000 - In Evangelos Dermatas (ed.), Proceedings of COMLEX2000: Computational lexicography. Patras University Press. pp. 141-144.
    Two large lexicological projects for the Center for the Greek Language, Thessaloniki, were to be published in print and on the WWW, which meant that two conversions were needed: a near-database file had to be converted to fully formatted file for printing and a fully formatted file had to be converted to a database for WWW access. As it turned out, both conversions could make use of existing clues that indicated the kinds of information contained in each particular piece of (...)
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  10. Computability and Human Symbolic Output.Jason Megill & Tim Melvin - 2014 - Logic and Logical Philosophy.
    This paper concerns “human symbolic output,” or strings of characters produced by humans in our various symbolic systems; e.g., sentences in a natural language, mathematical propositions, and so on. One can form a set that consists of all of the strings of characters that have been produced by at least one human up to any given moment in human history. We argue that at any particular moment in human history, even at moments in the distant future, this set is finite. (...)
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  11. Fundamental Issues of Artificial Intelligence.Vincent Müller (ed.) - 2016 - 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 (...)
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  12. Mind and Machine.Cathal O’Madagain - 2014 - International Journal of Philosophical Studies 22 (2):291-295.
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  13. Philosophy and Theory of Artificial Intelligence.Vincent C. 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 (...)
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  14. Is There a Future for AI Without Representation?Vincent C. Müller - 2007 - Minds and Machines 17 (1):101-115.
    This paper investigates the prospects of Rodney Brooks’ proposal for AI without representation. It turns out that the supposedly characteristic features of “new AI” (embodiment, situatedness, absence of reasoning, and absence of representation) are all present in conventional systems: “New AI” is just like old AI. Brooks proposal boils down to the architectural rejection of central control in intelligent agents—Which, however, turns out to be crucial. Some of more recent cognitive science suggests that we might do well to dispose of (...)
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  15. Margaret A. Boden, Mind as Machine: A History of Cognitive Science , 2 Vols. [REVIEW]Vincent C. Müller - 2008 - Minds and Machines 18 (1):121-125.
    Review of: Margaret A. Boden, Mind as Machine: A History of Cognitive Science, 2 vols, Oxford: Oxford University Press, 2006, xlvii+1631, cloth $225, ISBN 0-19-924144-9. - Mind as Machine is Margaret Boden’s opus magnum. For one thing, it comes in two massive volumes of nearly 1700 pages, ... But it is not just the opus magnum in simple terms of size, but also a truly crowning achievement of half a century’s career in cognitive science.
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  16. Minds and Machines.Hilary Putnam - 1960 - In Sidney Hook (ed.), Journal of Symbolic Logic. New York University Press. pp. 57-80.
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  17. Understanding Understanding: Syntactic Semantics and Computational Cognition.William J. Rapaport - 1995 - Philosophical Perspectives 9:49-88.
    John Searle once said: "The Chinese room shows what we knew all along: syntax by itself is not sufficient for semantics. (Does anyone actually deny this point, I mean straight out? Is anyone actually willing to say, straight out, that they think that syntax, in the sense of formal symbols, is really the same as semantic content, in the sense of meanings, thought contents, understanding, etc.?)." I say: "Yes". Stuart C. Shapiro has said: "Does that make any sense? Yes: Everything (...)
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The Turing Test
  1. Review of I Am a Strange Loop by Douglas Hofstadter (2007) (Review Revised 2019).Michael Starks - 2019 - In Suicidal Utopian Delusions in the 21st Century-- Philosophy, Human Nature and the Collapse of Civilization -- Articles and Reviews 2006-2019 4th Edition Michael Starks. Las Vegas, NV USA: Reality Press. pp. 217-235.
    Latest Sermon from the Church of Fundamentalist Naturalism by Pastor Hofstadter. Like his much more famous (or infamous for its relentless philosophical errors) work Godel, Escher, Bach, it has a superficial plausibility but if one understands that this is rampant scientism which mixes real scientific issues with philosophical ones (i.e., the only real issues are what language games we ought to play) then almost all its interest disappears. I provide a framework for analysis based in evolutionary psychology and the work (...)
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  2. Davidson's No-Priority Thesis in Defending the Turing Test.Mohammad Reza Vaez Shahrestani - 2012 - Procedia - Social and Behavioral Sciences 32:456-461.
    Turing does not provide an explanation for substituting the original question of his test – i.e., “Can machines think?” with “Can a machine pass the imitation game?” – resulting in an argumentative gap in his main thesis. In this article, I argue that a positive answer to the second question would mean attributing the ability of linguistic interactions to machines; while a positive answer to the original question would mean attributing the ability of thinking to machines. In such a situation, (...)
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  3. Theses From CPHL709.Paul Bali - manuscript
    on synchronicity, the Fermi Paradox, the Turing Test, and more.
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  4. El test de Turing: dos mitos, un dogma.Rodrigo González - 2007 - Revista de Filosofía 63:37-53.
    Este artículo analiza el Test de Turing, uno de los métodos más famosos y controvertidos para evaluar la existencia de vida mental en la Filosofía de la Mente, revelando dos mitos filosóficos comúnmente aceptados y criticando su dogma. En primer lugar, se muestra por qué Turing nunca propuso una definición de inteligencia. En segundo lugar, se refuta que el Test de Turing involucre condiciones necesarias o suficientes para la inteligencia. En tercer lugar, teniendo presente el objetivo y el tipo de (...)
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  5. Review of The Emotion Machine by Marvin Minsky (2007).Michael Starks - 2016 - In Suicidal Utopian Delusions in the 21st Century: Philosophy, Human Nature and the Collapse of Civilization-- Articles and Reviews 2006-2017 2nd Edition Feb 2018. Michael Starks. pp. 627.
    Dullest book by a major scientist I have ever read. I suppose if you know almost nothing about cognition or AI research you might find this book useful. For anyone else it is a horrific bore. There are hundreds of books in cog sci, robotics, AI, evolutionary psychology and philosophy offering far more info and insight on cognition than this one. Minsky is a top rate senior scientist but it barely shows here. He has alot of good references but they (...)
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  6. The Imitation Game.John Mark Bishop - 2010 - Kybernetes 39 (3):398-402.
    This issue of the Kybernetes journal is concerned with the philosophical question- Can a Machine Think? Famously, in his 1950 paper `Computing Machinery andIntelligence' [9], the British mathematician Alan Turing suggested replacing this question - which he found \too meaningless to deserve discussion" - with a simple -behavioural - test based on an imagined `Victorianesque' pastime he entitled the`imitation game'. In this special issue of Kybernetes a selection of authors with a special interest in Turing's work (including those who participated (...)
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  7. Πενήντα χρόνια τεχνητής νοημοσύνης: γιατί δεν επιτύχαμε ακόμα; [Fifty years of artificial intelligence: Why have we not succeeded yet?].Vincent C. Müller - 2006 - Cogito 4:48-49.
    1 Οι Αρχές - 2 Η δοκιμασία του Turing - 3 Η κλασική τεχνητή νοημοσύνη - 4 Η τεχνητή νοημοσύνη σήμερα - 5 Η τεχνητή νοημοσύνη του μέλλοντος - Με τις τεχνολογίες του παρόντος μάλλον θα δυσκολευτούμε να φτάσουμε στην κατασκευή μηχανών με τεχνητή νοημοσύνη. Κατά την γνώμη μου, θα δούμε άλλες τεχνικές λύσεις με την κλασική τεχνητή νοημοσύνη και μέθοδο «από κάτω προς τα πάνω», αλλά δεν περιμένω να υπάρξει ριζοσπαστική πρόοδος πριν μάθουμε πολλά παραπάνω για τον εγκέφαλό μας. (...)
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  8. Test.R. E. Ives - manuscript
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  9. Revisiting Turing and His Test: Comprehensiveness, Qualia, and the Real World.Vincent C. Müller & Aladdin Ayesh (eds.) - 2012 - AISB.
    Proceedings of the papers presented at the Symposium on "Revisiting Turing and his Test: Comprehensiveness, Qualia, and the Real World" at the 2012 AISB and IACAP Symposium that was held in the Turing year 2012, 2–6 July at the University of Birmingham, UK. Ten papers. - http://www.pt-ai.org/turing-test --- Daniel Devatman Hromada: From Taxonomy of Turing Test-Consistent Scenarios Towards Attribution of Legal Status to Meta-modular Artificial Autonomous Agents - Michael Zillich: My Robot is Smarter than Your Robot: On the Need for (...)
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  10. Laws of Form and the Force of Function: Variations on the Turing Test.Hajo Greif - 2012 - In Vincent C. Müller & Aladdin Ayesh (eds.), Revisiting Turing and His Test: Comprehensiveness, Qualia, and the Real World. AISB. pp. 60-64.
    This paper commences from the critical observation that the Turing Test (TT) might not be best read as providing a definition or a genuine test of intelligence by proxy of a simulation of conversational behaviour. Firstly, the idea of a machine producing likenesses of this kind served a different purpose in Turing, namely providing a demonstrative simulation to elucidate the force and scope of his computational method, whose primary theoretical import lies within the realm of mathematics rather than cognitive modelling. (...)
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  11. A Novel Approach for Identifying a Human-Like Self-Conscious Behavior.Gianpiero Negri - manuscript
    In this paper a possible extension of Turing test [1] will be presented, which is intended to overcome the limits highlighted by several researchers and scientists in the last seventy years. The main problem related to the execution in Turing test is substantially dealing with the trouble in identification of a human-like intelligence based on a pure evaluation of external behavior of a machine. In this work first of all a description of classical Turing test will be done. After that, (...)
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  12. Was Roboter nicht können. Die Roboterantwort als knapp misslungene Verteidigung der starken KI-These.Geert Keil - 1998 - In Andreas Engel & Peter Gold (eds.), Der Mensch in der Perspektive der Kognitionswissenschaften. Suhrkamp. pp. 98-131.
    Theoretiker der Künstlichen Intelligenz und deren Wegbegleiter in der Philosophie des Geistes haben auf unterschiedliche Weise auf Kritik am ursprünglichen Theorieziel der KI reagiert. Eine dieser Reaktionen ist die Zurücknahme dieses Theorieziels zugunsten der Verfolgung kleinerformatiger Projekte. Eine andere Reaktion ist die Propagierung konnektionistischer Systeme, die mit ihrer dezentralen Arbeitsweise die neuronalen Netze des menschlichen Gehirns besser simulieren sollen. Eine weitere ist die sogenannte robot reply. Die Roboterantwort besteht aus zwei Elementen. Sie enthält (a) das Zugeständnis, daß das Systemverhalten eines (...)
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  13. Turing and the Evaluation of Intelligence.Francesco Bianchini - 2014 - Isonomia: Online Philosophical Journal of the University of Urbino:1-18.
    The article deals with some ideas by Turing concerning the background and the birth of the well-known Turing Test, showing the evolution of the main question proposed by Turing on thinking machine. The notions he used, especially that one of imitation, are not so much exactly defined and shaped, but for this very reason they have had a deep impact in artificial intelligence and cognitive science research from an epistemological point of view. Then, it is suggested that the fundamental concept (...)
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  14. Introduction to a Systemic Theory of Meaning (July 2014 Update).Christophe Menant - 2014 - Dissertation,
    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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  15. On the Claim That a Table-Lookup Program Could Pass the Turing Test.Drew McDermott - 2014 - Minds and Machines 24 (2):143-188.
    The claim has often been made that passing the Turing Test would not be sufficient to prove that a computer program was intelligent because a trivial program could do it, namely, the “Humongous-Table (HT) Program”, which simply looks up in a table what to say next. This claim is examined in detail. Three ground rules are argued for: (1) That the HT program must be exhaustive, and not be based on some vaguely imagined set of tricks. (2) That the HT (...)
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  16. Turing Test, Chinese Room Argument, Symbol Grounding Problem. Meanings in Artificial Agents (2013).Christophe Menant - 2013 - In The American Philosophical Associat ion (ed.), APA Newsletter Philosophy and Computers Fall 2013 ISSN 2155-9708. The American Philosophical Associat ion.
    The Turing Test (TT), the Chinese Room Argument (CRA), and the Symbol Grounding Problem (SGP) are about the question “can machines think?” We propose to look at these approaches to Artificial Intelligence (AI) by showing that they all address the possibility for Artificial Agents (AAs) to generate meaningful information (meanings) as we humans do. The initial question about thinking machines is then reformulated into “can AAs generate meanings like humans do?” We correspondingly present the TT, the CRA and the SGP (...)
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  17. Turing: A Formal Clash of Codes. Witzany & Baluska - 2012 - Nature 483:541.
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  18. Semiotic Systems, Computers, and the Mind: How Cognition Could Be Computing.William J. Rapaport - 2012 - International Journal of Signs and Semiotic Systems 2 (1):32-71.
    In this reply to James H. Fetzer’s “Minds and Machines: Limits to Simulations of Thought and Action”, I argue that computationalism should not be the view that (human) cognition is computation, but that it should be the view that cognition (simpliciter) is computable. It follows that computationalism can be true even if (human) cognition is not the result of computations in the brain. I also argue that, if semiotic systems are systems that interpret signs, then both humans and computers are (...)
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  19. Computers, Persons, and the Chinese Room. Part 2: Testing Computational Cognitive Science.Ricardo Restrepo - 2012 - Journal of Mind and Behavior 33 (3):123-140.
    This paper is a follow-up of the first part of the persons reply to the Chinese Room Argument. The first part claims that the mental properties of the person appearing in that argument are what matter to whether computational cognitive science is true. This paper tries to discern what those mental properties are by applying a series of hypothetical psychological and strengthened Turing tests to the person, and argues that the results support the thesis that the Man performing the computations (...)
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  20. Computers, Persons, and the Chinese Room. Part 1: The Human Computer.Ricardo Restrepo - 2012 - Journal of Mind and Behavior 33 (1):27-48.
    Detractors of Searle’s Chinese Room Argument have arrived at a virtual consensus that the mental properties of the Man performing the computations stipulated by the argument are irrelevant to whether computational cognitive science is true. This paper challenges this virtual consensus to argue for the first of the two main theses of the persons reply, namely, that the mental properties of the Man are what matter. It does this by challenging many of the arguments and conceptions put forth by the (...)
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  21. Philosophy of Mind Is (in Part) Philosophy of Computer Science.Darren Abramson - 2011 - Minds and Machines 21 (2):203-219.
    In this paper I argue that whether or not a computer can be built that passes the Turing test is a central question in the philosophy of mind. Then I show that the possibility of building such a computer depends on open questions in the philosophy of computer science: the physical Church-Turing thesis and the extended Church-Turing thesis. I use the link between the issues identified in philosophy of mind and philosophy of computer science to respond to a prominent argument (...)
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  22. Yes, She Was! Reply to Ford’s “Helen KellerWas Never in a Chinese Room”.William Rapaport - 2011 - Minds and Machines 21 (1):3-17.
    Ford’s Helen Keller Was Never in a Chinese Room claims that my argument in How Helen Keller Used Syntactic Semantics to Escape from a Chinese Room fails because Searle and I use the terms ‘syntax’ and ‘semantics’ differently, hence are at cross purposes. Ford has misunderstood me; this reply clarifies my theory.
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  23. Yes, She Was! Reply to Ford’s “Helen KellerWas Never in a Chinese Room”.William Rapaport - 2011 - Minds and Machines 21 (1):3-17.
    Ford’s Helen Keller Was Never in a Chinese Room claims that my argument in How Helen Keller Used Syntactic Semantics to Escape from a Chinese Room fails because Searle and I use the terms ‘syntax’ and ‘semantics’ differently, hence are at cross purposes. Ford has misunderstood me; this reply clarifies my theory.
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  24. Vindication of the Rights of Machine.Kris Rhodes - manuscript
    In this paper, I argue that certain Machines can have rights independently of whether they are sentient, or conscious, or whatever you might call it.
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  25. Wittgenstein and the Aesthetic Robot's Handicap.Julian Friedland - 2005 - Philosophical Investigations 28 (2):177-192.
    Ask most any cognitive scientist working today if a digital computational system could develop aesthetic sensibility and you will likely receive the optimistic reply that this remains an open empirical question. However, I attempt to show, while drawing upon the later Wittgenstein, that the correct answer is in fact available. And it is a negative a priori. It would seem, for example, that recent computational successes in textual attribution, most notably those of Donald Foster (famed finder of Ted Kazinski a.k.a. (...)
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  26. On the Verisimilitude of Artificial Intelligence.Roger Vergauwen & Rodrigo González - 2005 - Logique Et Analyse- 190 (189):323-350.
    This paper investigates how the simulation of intelligence, an activity that has been considered the notional task of Artificial Intelligence, does not comprise its duplication. Briefly touching on the distinction between conceivability and possibility, and commenting on Ryan’s approach to fiction in terms of the interplay between possible worlds and her principle of minimal departure, we specify verisimilitude in Artificial Intelligence as the accurate resemblance of intelligence by its simulation and, from this characterization, claim the metaphysical impossibility of duplicating intelligence, (...)
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Godelian Arguments Against AI
  1. Review of I Am a Strange Loop by Douglas Hofstadter (2007) (Review Revised 2019).Michael Starks - 2019 - In Suicidal Utopian Delusions in the 21st Century-- Philosophy, Human Nature and the Collapse of Civilization -- Articles and Reviews 2006-2019 4th Edition Michael Starks. Las Vegas, NV USA: Reality Press. pp. 217-235.
    Latest Sermon from the Church of Fundamentalist Naturalism by Pastor Hofstadter. Like his much more famous (or infamous for its relentless philosophical errors) work Godel, Escher, Bach, it has a superficial plausibility but if one understands that this is rampant scientism which mixes real scientific issues with philosophical ones (i.e., the only real issues are what language games we ought to play) then almost all its interest disappears. I provide a framework for analysis based in evolutionary psychology and the work (...)
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  2. Gödel’s Disjunction: The Scope and Limits of Mathematical Knowledge. [REVIEW]Panu Raatikainen - 2018 - History and Philosophy of Logic 39 (4):401-403.
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  3. Turing Machines and Semantic Symbol Processing: Why Real Computers Don’T Mind Chinese Emperors.Richard Yee - 1993 - Lyceum 5 (1):37-59.
    Philosophical questions about minds and computation need to focus squarely on the mathematical theory of Turing machines (TM's). Surrogate TM's such as computers or formal systems lack abilities that make Turing machines promising candidates for possessors of minds. Computers are only universal Turing machines (UTM's)—a conspicuous but unrepresentative subclass of TM. Formal systems are only static TM's, which do not receive inputs from external sources. The theory of TM computation clearly exposes the failings of two prominent critiques, Searle's Chinese room (...)
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  4. A Machine That Knows Its Own Code.Samuel A. Alexander - 2014 - Studia Logica 102 (3):567-576.
    We construct a machine that knows its own code, at the price of not knowing its own factivity.
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  5. Roger Penrose, The Large, the Small and the Human Mind. [REVIEW]B. Josephson - 1997 - Journal of Consciousness Studies 4:271-273.
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  6. This Sentence Does Not Contain the Symbol X.Samuel Alexander - 2013 - The Reasoner 7 (9):108.
    A suprise may occur if we use a similar strategy to the Liar's paradox to mathematically formalize "This sentence does not contain the symbol X".
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  7. Truth and Provability Again.Jeffrey Ketland & Panu Raatikainen - manuscript
    Lucas and Redhead ([2007]) announce that they will defend the views of Redhead ([2004]) against the argument by Panu Raatikainen ([2005]). They certainly re-state the main claims of Redhead ([2004]), but they do not give any real arguments in their favour, and do not provide anything that would save Redhead’s argument from the serious problems pointed out in (Raatikainen [2005]). Instead, Lucas and Redhead make a number of seemingly irrelevant points, perhaps indicating a failure to understand the logico-mathematical points at (...)
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