Results for 'Turing Halting Problem'

998 found
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  1. Halting Problem Proof from Finite Strings to Final States.P. Olcott - manuscript
    If there truly is a proof that shows that no universal halt decider exists on the basis that certain tuples: (H, Wm, W) are undecidable, then this very same proof (implemented as a Turing machine) could be used by H to reject some of its inputs. When-so-ever the hypothetical halt decider cannot derive a formal proof from its input strings and initial state to final states corresponding the mathematical logic functions of Halts(Wm, W) or Loops(Wm, W), halting undecidability (...)
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  2. Arithmetic logical Irreversibility and the Halting Problem (Revised and Fixed version).Yair Lapin - manuscript
    The Turing machine halting problem can be explained by several factors, including arithmetic logic irreversibility and memory erasure, which contribute to computational uncertainty due to information loss during computation. Essentially, this means that an algorithm can only preserve information about an input, rather than generate new information. This uncertainty arises from characteristics such as arithmetic logical irreversibility, Landauer's principle, and memory erasure, which ultimately lead to a loss of information and an increase in entropy. To measure this (...)
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  3. Defining a Decidability Decider for the Halting Problem.P. Olcott - manuscript
    When we understand that every potential halt decider must derive a formal mathematical proof from its inputs to its final states previously undiscovered semantic details emerge. -/- When-so-ever the potential halt decider cannot derive a formal proof from its input strings to its final states of Halts or Loops, undecidability has been decided. -/- The formal proof involves tracing the sequence of state transitions of the input TMD as syntactic logical consequence inference steps in the formal language of Turing (...)
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  4.  85
    Simulating Halt Deciders Defeat the Halting Theorem.P. Olcott - manuscript
    The novel concept of a simulating halt decider enables halt decider H to to correctly determine the halt status of the conventional “impossible” input D that does the opposite of whatever H decides. This works equally well for Turing machines and “C” functions. The algorithm is demonstrated using “C” functions because all of the details can be shown at this high level of abstraction.
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  5. Simulating Halt Decider Applied to the Halting Theorem.P. Olcott - manuscript
    The novel concept of a simulating halt decider enables halt decider H to to correctly determine the halt status of the conventional “impossible” input D that does the opposite of whatever H decides. This works equally well for Turing machines and “C” functions. The algorithm is demonstrated using “C” functions because all of the details can be shown at this high level of abstraction. ---------------------------------------------------------------------------------------------------- ---- Simulating halt decider H correctly determines that D correctly simulated by H would remain stuck (...)
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  6. Halting problem undecidability and infinitely nested simulation.P. Olcott - manuscript
    The halting theorem counter-examples present infinitely nested simulation (non-halting) behavior to every simulating halt decider. The pathological self-reference of the conventional halting problem proof counter-examples is overcome. The halt status of these examples is correctly determined. A simulating halt decider remains in pure simulation mode until after it determines that its input will never reach its final state. This eliminates the conventional feedback loop where the behavior of the halt decider effects the behavior of its input.
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  7. Halting problem proofs refuted on the basis of software engineering ?P. Olcott - manuscript
    This is an explanation of a possible new insight into the halting problem provided in the language of software engineering. Technical computer science terms are explained using software engineering terms. No knowledge of the halting problem is required. -/- It is based on fully operational software executed in the x86utm operating system. The x86utm operating system (based on an excellent open source x86 emulator) was created to study the details of the halting problem proof (...)
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  8. Halting problem undecidability and infinitely nested simulation (V3).P. Olcott - manuscript
    By making a slight refinement to the halt status criterion measure that remains consistent with the original a halt decider may be defined that correctly determines the halt status of the conventional halting problem proof counter-examples. This refinement overcomes the pathological self-reference issue that previously prevented halting decidability.
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  9. Halting problem undecidability and infinitely nested simulation (V2).P. Olcott - manuscript
    The halting theorem counter-examples present infinitely nested simulation (non-halting) behavior to every simulating halt decider. Whenever the pure simulation of the input to simulating halt decider H(x,y) never stops running unless H aborts its simulation H correctly aborts this simulation and returns 0 for not halting.
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  10. Halting problem undecidability and infinitely nested simulation (V5).P. Olcott - manuscript
    This is an explanation of a key new insight into the halting problem provided in the language of software engineering. Technical computer science terms are explained using software engineering terms. -/- To fully understand this paper a software engineer must be an expert in the C programming language, the x86 programming language, exactly how C translates into x86 and what an x86 process emulator is. No knowledge of the halting problem is required.
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  11. Halting problem undecidability and infinitely nested simulation (V4).P. Olcott - manuscript
    A Simulating Halt Decider (SHD) computes the mapping from its input to its own accept or reject state based on whether or not the input simulated by a UTM would reach its final state in a finite number of simulated steps. -/- A halt decider (because it is a decider) must report on the behavior specified by its finite string input. This is its actual behavior when it is simulated by the UTM contained within its simulating halt decider while this (...)
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  12. Representation and Reality by Language: How to make a home quantum computer?Vasil Penchev - 2020 - Philosophy of Science eJournal (Elsevier: SSRN) 13 (34):1-14.
    A set theory model of reality, representation and language based on the relation of completeness and incompleteness is explored. The problem of completeness of mathematics is linked to its counterpart in quantum mechanics. That model includes two Peano arithmetics or Turing machines independent of each other. The complex Hilbert space underlying quantum mechanics as the base of its mathematical formalism is interpreted as a generalization of Peano arithmetic: It is a doubled infinite set of doubled Peano arithmetics having (...)
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  13. Does the halting problem place an actual limit on computation?P. Olcott - manuscript
    Hehner and Stoddart agree that the halting problem has an inconsistent, unsatisfiable specification. Hehner and Macias agree that a key issue with the halting problem is that it requires a: subjective specification(Hehner) / context dependent function(Macias). When a problem has an unsatisfiable specification because this specification is inconsistent then the unsatisfiability of the specification is anchored in its error thus does not actually limit computation.
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  14. Rebutting the Sipser Halting Problem Proof V2.P. Olcott - manuscript
    A simulating halt decider correctly predicts what the behavior of its input would be if this simulated input never had its simulation aborted. It does this by correctly recognizing several non-halting behavior patterns in a finite number of steps of correct simulation. -/- When simulating halt decider H correctly predicts that directly executed D(D) would remain stuck in recursive simulation (run forever) unless H aborts its simulation of D this directly applies to the halting theorem.
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  15. Rebutting the Sipser Halting Problem Proof.P. Olcott - manuscript
    MIT Professor Michael Sipser has agreed that the following verbatim paragraph is correct (he has not agreed to anything else in this paper) -------> -/- If simulating halt decider H correctly simulates its input D until H correctly determines that its simulated D would never stop running unless aborted then H can abort its simulation of D and correctly report that D specifies a non-halting sequence of configurations.
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  16. Equivalence of the Frame and Halting Problems.Eric Dietrich & Chris Fields - 2020 - Algorithms 13 (175):1-9.
    The open-domain Frame Problem is the problem of determining what features of an open task environment need to be updated following an action. Here we prove that the open-domain Frame Problem is equivalent to the Halting Problem and is therefore undecidable. We discuss two other open-domain problems closely related to the Frame Problem, the system identification problem and the symbol-grounding problem, and show that they are similarly undecidable. We then reformulate the Frame (...)
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  17. Simulating (partial) Halt Deciders Defeat the Halting Problem Proofs.P. Olcott - manuscript
    A simulating halt decider correctly predicts whether or not its correctly simulated input can possibly reach its own final state and halt. It does this by correctly recognizing several non-halting behavior patterns in a finite number of steps of correct simulation. Inputs that do terminate are simply simulated until they complete.
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  18. Ideal Negative Conceivability and the Halting Problem.Manolo Martínez - 2013 - Erkenntnis 78 (5):979-990.
    Our limited a priori-reasoning skills open a gap between our finding a proposition conceivable and its metaphysical possibility. A prominent strategy for closing this gap is the postulation of ideal conceivers, who suffer from no such limitations. In this paper I argue that, under many, maybe all, plausible unpackings of the notion of ideal conceiver, it is false that ideal negative conceivability entails possibility.
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  19. When Should We Stop Investing in a Scientific Project? The Halting Problem in Experimental Physics.Vlasta Sikimić, Sandro Radovanović & Slobodan Perovic - 2018 - In Kaja Damnjanović, Ivana Stepanović Ilić & Slobodan Marković (eds.), Proceedings of the XXIV Conference “Empirical Studies in Psychology”. Belgrade, Serbia: pp. 105-107.
    The question of when to stop an unsuccessful experiment can be difficult to answer from an individual perspective. To help to guide these decisions, we turn to the social epistemology of science and investigate knowledge inquisition within a group. We focused on the expensive and lengthy experiments in high energy physics, which were suitable for citation-based analysis because of the relatively quick and reliable consensus about the importance of results in the field. In particular, we tested whether the time spent (...)
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  20. A Mathematical Model of Quantum Computer by Both Arithmetic and Set Theory.Vasil Penchev - 2020 - Information Theory and Research eJournal 1 (15):1-13.
    A practical viewpoint links reality, representation, and language to calculation by the concept of Turing (1936) machine being the mathematical model of our computers. After the Gödel incompleteness theorems (1931) or the insolvability of the so-called halting problem (Turing 1936; Church 1936) as to a classical machine of Turing, one of the simplest hypotheses is completeness to be suggested for two ones. That is consistent with the provability of completeness by means of two independent Peano (...)
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  21. Sets, Logic, Computation: An Open Introduction to Metalogic.Richard Zach - 2021 - Open Logic Project.
    An introductory textbook on metalogic. It covers naive set theory, first-order logic, sequent calculus and natural deduction, the completeness, compactness, and Löwenheim-Skolem theorems, Turing machines, and the undecidability of the halting problem and of first-order logic. The audience is undergraduate students with some background in formal logic.
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  22. Turing Test, Chinese Room Argument, Symbol Grounding Problem. Meanings in Artificial Agents (APA 2013).Christophe Menant - 2013 - American Philosophical Association Newsletter on Philosophy and Computers 13 (1):30-34.
    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 (...)
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  23. Termination Analyzer H is Not Fooled by Pathological Input D.P. Olcott - manuscript
    A pair of C functions are defined such that D has the halting problem proof's pathological relationship to simulating termination analyzer H. When H correctly determines that D correctly simulated by H must be aborted to prevent its own infinite execution then H is necessarily correct to reject D as specifying non-halting behavior. This exact same reasoning is applied to the Peter Linz Turing machine based halting problem proof. ...
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  24. Counterpossibles in Science: The Case of Relative Computability.Matthias Jenny - 2018 - Noûs 52 (3):530-560.
    I develop a theory of counterfactuals about relative computability, i.e. counterfactuals such as 'If the validity problem were algorithmically decidable, then the halting problem would also be algorithmically decidable,' which is true, and 'If the validity problem were algorithmically decidable, then arithmetical truth would also be algorithmically decidable,' which is false. These counterfactuals are counterpossibles, i.e. they have metaphysically impossible antecedents. They thus pose a challenge to the orthodoxy about counterfactuals, which would treat them as uniformly (...)
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  25. On Turing Completeness, or Why We Are So Many (7th edition).Ramón Casares - manuscript
    Why are we so many? Or, in other words, Why is our species so successful? The ultimate cause of our success as species is that we, Homo sapiens, are the first and the only Turing complete species. Turing completeness is the capacity of some hardware to compute by software whatever hardware can compute. To reach the answer, I propose to see evolution and computing from the problem solving point of view. Then, solving more problems is evolutionarily better, (...)
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  26. Turing test: 50 years later.Ayse Pinar Saygin, Ilyas Cicekli & Varol Akman - 2000 - Minds and Machines 10 (4):463-518.
    The Turing Test is one of the most disputed topics in artificial intelligence, philosophy of mind, and cognitive science. This paper is a review of the past 50 years of the Turing Test. Philosophical debates, practical developments and repercussions in related disciplines are all covered. We discuss Turing's ideas in detail and present the important comments that have been made on them. Within this context, behaviorism, consciousness, the 'other minds' problem, and similar topics in philosophy of (...)
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  27. Turing and Computationalism.Napoleon M. Mabaquiao - 2014 - Philosophia: International Journal of Philosophy (Philippine e-journal) 15 (1):50-62.
    Due to his significant role in the development of computer technology and the discipline of artificial intelligence, Alan Turing has supposedly subscribed to the theory of mind that has been greatly inspired by the power of the said technology which has eventually become the dominant framework for current researches in artificial intelligence and cognitive science, namely, computationalism or the computational theory of mind. In this essay, I challenge this supposition. In particular, I will try to show that there is (...)
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  28. Halted Democracy: Government Hijacking of the New Opposition in Azerbaijan.Altay Goyushov & Ilkin Huseynli - 2019 - In Olaf Leiße (ed.), Politik und Gesellschaft im Kaukasus: Eine unruhige Region zwischen Tradition und Transformation. Wiesbaden, Germany: Springer VS. pp. 27-51.
    We argue that while the new opposition in Azerbaijan between 2005 and 2013 did not realize all the goals set, it influenced a new generation of young activists who became the loudest supporters of democratic and secular values in Azerbaijan. This grassroots activation of the youth brought noticeable changes to some parts of Azerbaijani society by questioning the authority of traditional values. Many young people, especially students found a platform to discuss their problems concerning everyday basic issues such as intimate (...)
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  29. An Empathy Imitation Game: Empathy Turing Test for Care- and Chat-bots.Jeremy Howick, Jessica Morley & Luciano Floridi - 2021 - Minds and Machines 31 (3):1–⁠5.
    AI, in the form of artificial carers, provides a possible solution to the problem of a growing elderly population Yet, concerns remain that artificial carers ( such as care-or chat-bots) could not emphathize with patients to the extent that humans can. Utilising the concept of empathy perception,we propose a Turing-type test that could check whether artificial carers could do many of the menial tasks human carers currently undertake, and in the process, free up more time for doctors to (...)
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  30. Minimum Intelligent Signal Test as an Alternative to the Turing Test.Paweł Łupkowski & Patrycja Jurowska - 2019 - Diametros 59:35-47.
    The aim of this paper is to present and discuss the issue of the adequacy of the Minimum Intelligent Signal Test (MIST) as an alternative to the Turing Test. MIST has been proposed by Chris McKinstry as a better alternative to Turing’s original idea. Two of the main claims about MIST are that (1) MIST questions exploit commonsense knowledge and as a result are expected to be easy to answer for human beings and difficult for computer programs; and (...)
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  31. The Many Problems of Distal Olfactory Perception.Benjamin D. Young - 2019 - In Tony Cheng, Ophelia Deroy & Charles Spence (eds.), Spatial Senses: Philosophy of Perception in an Age of Science. Routledge Press.
    The chapter unfolds in the following sections. The first section exam- ines the reasons for claiming that olfactory perception is spatially unstruc- tured and our experience of smells has an abstract structure. The second section elucidates the further arguments that olfaction cannot generate figure-ground segregation. The third section assesses the conclusion that olfactory perception and experience cannot solve the MPP. Following the overview of the many problems inherent to distal olfactory percep- tion, MST will be introduced as an alternative perspective (...)
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  32. Consistency Problem and “Unexpected Hanging Paradox” (An answering to P=NP Problem).Farzad Didehvar - unknown
    Abstract The Theory of Computation in its existed form is based on Church –Turing Thesis. Throughout this paper, we show that the Turing computation model of this theory leads us to a contradiction. In brief, by applying a well-known paradox (Unexpected hanging paradox) we show a contradiction in the Theory when we consider the Turing model as our Computation model.
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  33. Only Human: a book review of The Turing Guide. [REVIEW]Bjørn Kjos-Hanssen - forthcoming - Notices of the American Mathematical Society 66 (4).
    This is a review of The Turing Guide (2017), written by Jack Copeland, Jonathan Bowen, Mark Sprevak, Robin Wilson, and others. The review includes a new sociological approach to the problem of computability in physics.
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  34.  96
    The Decision Problem for Effective Procedures.Nathan Salmón - 2023 - Logica Universalis 17 (2):161-174.
    The “somewhat vague, intuitive” notion from computability theory of an effective procedure (method) or algorithm can be fairly precisely defined even if it is not sufficiently formal and precise to belong to mathematics proper (in a narrow sense)—and even if (as many have asserted) for that reason the Church–Turing thesis is unprovable. It is proved logically that the class of effective procedures is not decidable, i.e., that there is no effective procedure for ascertaining whether a given procedure is effective. (...)
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  35. Wolpert, Chaitin y Wittgenstein sobre la imposibilidad, la incompletitud, la paradoja mentirosa, el teísmo, los límites de la computación, un principio de incertidumbre mecánica no cuántica y el universo como computadora, el teorema definitivo en la teoría de la máquina de Turing (revisado en 2019).Michael Richard Starks - 2019 - In OBSERVACIONES SOBRE IMPOSIBILIDAD, INCOMPLETA, PARACOHERENCIA,INDECISIÓN,ALEATORIEDAD, COMPUTABILIDAD, PARADOJA E INCERTIDUMBRE EN CHAITIN, WITTGENSTEIN, HOFSTADTER, WOLPERT, DORIA, DACOSTA, GODEL, SEARLE, RODYCH, BERTO,FLOYD, MOYAL-SHARROCK Y YANOFSKY. Reality Press. pp. 64-70.
    It is commonly thought that Impossibility, Incompleteness, Paraconsistency, Undecidability, Randomness, Computability, Paradox, Uncertainty and the Limits of Reason are disparate scientific physical or mathematical issues having little or nothing in common. I suggest that they are largely standard philosophical problems (i.e., language games) which were mostly resolved by Wittgenstein over 80years ago. -/- “What we are ‘tempted to say’ in such a case is, of course, not philosophy, but it is its raw material. Thus, for example, what a mathematician is (...)
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  36. Classical AI linguistic understanding and the insoluble Cartesian problem.Rodrigo González - 2020 - AI and Society 35 (2):441-450.
    This paper examines an insoluble Cartesian problem for classical AI, namely, how linguistic understanding involves knowledge and awareness of u’s meaning, a cognitive process that is irreducible to algorithms. As analyzed, Descartes’ view about reason and intelligence has paradoxically encouraged certain classical AI researchers to suppose that linguistic understanding suffices for machine intelligence. Several advocates of the Turing Test, for example, assume that linguistic understanding only comprises computational processes which can be recursively decomposed into algorithmic mechanisms. Against this (...)
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  37. Epistemic Perceptualism, Skill, and the Regress Problem.J. Adam Carter - 2019 - Philosophical Studies:1-26.
    A novel solution is offered for how emotional experiences can function as sources of immediate prima facie justification for evaluative beliefs, and in such a way that suffices to halt a justificatory regress. Key to this solution is the recognition of two distinct kinds of emotional skill (what I call generative emotional skill and doxastic emotional skill) and how these must be working in tandem when emotional experience plays such a justificatory role. The paper has two main parts, the first (...)
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  38. Efficacy of Colistin Therapy in Patients with Hematological Malignancies: What if There is Colistin Resistance?Zeynep Ture, Gamze Kalın Unüvar, Hüseyin Nadir Kahveci, Muzaffer Keklik & Ayşegül Ulu Kilic - 2023 - European Journal of Therapeutics 29 (1):17-22.
    Objective: The objective of this study was to evaluate the clinical efficacy and appropriateness of colistin therapy in patients with hematological malignancies. -/- Methods: Age, gender, type of hematologic malignancy, and potential carbapenem-resistant microorganism risk factors were all noted in this retrospective study. In empirical and agent-specific treatment groups, differences in demographic features, risk factors, treatment responses, and side effects were compared. -/- Results: Sixty-three patients were included, 54% were male, and the median age was 49. In the last three (...)
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  39. National Defence, Self Defence, and the Problem of Political Aggression.Seth Lazar - 2014 - In Cécile Fabre & Seth Lazar (eds.), The Morality of Defensive War. Oxford, GB: Oxford University Press. pp. 10-38.
    Wars are large-scale conflicts between organized groups of belligerents, which involve suffering, devastation, and brutality unlike almost anything else in human experience. Whatever one’s other beliefs about morality, all should agree that the horrors of war are all but unconscionable, and that warfare can be justified only if we have some compel- ling account of what is worth fighting for, which can justify contributing, as individu- als and as groups, to this calamitous endeavour. Although this question should obviously be central (...)
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  40. Experimental Methods for Unraveling the Mind-body Problem: The Phenomenal Judgment Approach.Victor Argonov - 2014 - Journal of Mind and Behavior 35 (1-2):51-70.
    A rigorous approach to the study of the mind–body problem is suggested. Since humans are able to talk about consciousness (produce phenomenal judgments), it is argued that the study of neural mechanisms of phenomenal judgments can solve the hard problem of consciousness. Particular methods are suggested for: (1) verification and falsification of materialism; (2) verification and falsification of interactionism; (3) falsification of epiphenomenalism and parallelism (verification is problematic); (4) verification of particular materialistic theories of consciousness; (5) a non- (...) test for machine consciousness. A complex research program is constructed that includes studies of intelligent machines, numerical models of human and artificial creatures, language, neural correlates of con- sciousness, and quantum mechanisms in brain. (shrink)
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  41. A Class of Examples Demonstrating That 'P ≠ NP' in the 'P Vs NP' Problem.Vasil Penchev - 2020 - Computing Methodology eJournal (Elsevier: SSRN) 3 (19):1-19.
    The CMI Millennium “P vs NP Problem” can be resolved e.g. if one shows at least one counterexample to the "P = NP" conjecture. A certain class of problems being such counterexamples will be formulated. This implies the rejection of the hypothesis that "P = NP" for any conditions satisfying the formulation of the problem. Thus, the solution "P is different from NP" of the problem in general is proved. The class of counterexamples can be interpreted as (...)
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  42.  71
    Effective Procedures.Nathan Salmon - 2023 - Philosophies 8 (2):27.
    This is a non-technical version of "The Decision Problem for Effective Procedures." The “somewhat vague, intuitive” notion from computability theory of an effective procedure (method) or algorithm can be fairly precisely defined, even if it does not have a purely mathematical definition—and even if (as many have asserted) for that reason, the Church–Turing thesis (that the effectively calculable functions on natural numbers are exactly the general recursive functions), cannot be proved. However, it is logically provable from the notion (...)
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  43. How does Artificial Intelligence Pose an Existential Risk?Karina Vold & Daniel R. Harris - 2023 - In Carissa Véliz (ed.), The Oxford Handbook of Digital Ethics. Oxford University Press.
    Alan Turing, one of the fathers of computing, warned that Artificial Intelligence (AI) could one day pose an existential risk to humanity. Today, recent advancements in the field AI have been accompanied by a renewed set of existential warnings. But what exactly constitutes an existential risk? And how exactly does AI pose such a threat? In this chapter we aim to answer these questions. In particular, we will critically explore three commonly cited reasons for thinking that AI poses an (...)
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  44. The Significance of Evidence-based Reasoning in Mathematics, Mathematics Education, Philosophy, and the Natural Sciences.Bhupinder Singh Anand - 2020 - Mumbai: DBA Publishing (First Edition).
    In this multi-disciplinary investigation we show how an evidence-based perspective of quantification---in terms of algorithmic verifiability and algorithmic computability---admits evidence-based definitions of well-definedness and effective computability, which yield two unarguably constructive interpretations of the first-order Peano Arithmetic PA---over the structure N of the natural numbers---that are complementary, not contradictory. The first yields the weak, standard, interpretation of PA over N, which is well-defined with respect to assignments of algorithmically verifiable Tarskian truth values to the formulas of PA under the interpretation. (...)
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  45. MICHAEL POLANYI: CAN THE MIND BE REPRESENTED BY A MACHINE?Paul Richard Blum - 2010 - Polanyiana 19 (1-2):35-60.
    In 1949, the Department of Philosophy at the University of Manchester organized a symposium “Mind and Machine” with Michael Polanyi, the mathematicians Alan Turing and Max Newman, the neurologists Geoff rey Jeff erson and J. Z. Young, and others as participants. Th is event is known among Turing scholars, because it laid the seed for Turing’s famous paper on “Computing Machinery and Intelligence”, but it is scarcely documented. Here, the transcript of this event, together with Polanyi’s original (...)
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  46. Emergence and Computation at the Edge of Classical and Quantum Systems.Ignazio Licata - 2008 - In World Scientific (ed.), Physics of Emergence and Organization. World Scientific.
    The problem of emergence in physical theories makes necessary to build a general theory of the relationships between the observed system and the observing system. It can be shown that there exists a correspondence between classical systems and computational dynamics according to the Shannon-Turing model. A classical system is an informational closed system with respect to the observer; this characterizes the emergent processes in classical physics as phenomenological emergence. In quantum systems, the analysis based on the computation theory (...)
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  47. Informatics: Science or Téchne?Tito Palmeiro - 2016 - O Que Nos Faz Pensar 25:88-97.
    Informatics is generally understood as a “new technology” and is therewith discussed according to technological aspects such as speed, data retrieval, information control and so on. Its widespread use from home appliances to enterprises and universities is not the result of a clear-cut analysis of its inner possibilities but is rather dependent on all sorts of ideological promises of unlimited progress. We will discuss the theoretical definition of informatics proposed in 1936 by Alan Turing in order to show that (...)
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  48. Epistemological solipsism as a route to external world skepticism.Grace Helton - 2021 - Philosophical Perspectives 35 (1):229-250.
    I show that some of the most initially attractive routes of refuting epistemological solipsism face serious obstacles. I also argue that for creatures like ourselves, solipsism is a genuine form of external world skepticism. I suggest that together these claims suggest the following morals: No proposed solution to external world skepticism can succeed which does not also solve the problem of epistemological solipsism. And, more tentatively: In assessing proposed solutions to external world skepticism, epistemologists should explicitly consider whether those (...)
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  49. Towards a Theory of Computation similar to some other scientific theories.Antonino Drago - manuscript
    At first sight the Theory of Computation i) relies on a kind of mathematics based on the notion of potential infinity; ii) its theoretical organization is irreducible to an axiomatic one; rather it is organized in order to solve a problem: “What is a computation?”; iii) it makes essential use of doubly negated propositions of non-classical logic, in particular in the word expressions of the Church-Turing’s thesis; iv) its arguments include ad absurdum proofs. Under such aspects, it is (...)
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  50. Epistemic Modality and Hyperintensionality in Mathematics.Timothy Bowen - 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, (...)
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