Results for 'computation'

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  1. European Computing and Philosophy.Gordana Dodig-Crnkovic - 2009 - The Reasoner 3 (9):18-19.
    European Computing and Philosophy conference, 2–4 July Barcelona The Seventh ECAP (European Computing and Philosophy) conference was organized by Jordi Vallverdu at Autonomous University of Barcelona. The conference started with the IACAP (The International Association for CAP) presidential address by Luciano Floridi, focusing on mechanisms of knowledge production in informational networks. The first keynote delivered by Klaus Mainzer made a frame for the rest of the conference, by elucidating the fundamental role of complexity of informational structures that can be analyzed (...)
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  2. Membrane Computing: From Biology to Computation and Back.Paolo Milazzo - 2014 - Isonomia: Online Philosophical Journal of the University of Urbino:1-15.
    Natural Computing is a field of research in Computer Science aimed at reinterpreting biological phenomena as computing mechanisms. This allows unconventional computing architectures to be proposed in which computations are performed by atoms, DNA strands, cells, insects or other biological elements. Membrane Computing is a branch of Natural Computing in which biological phenomena of interest are related with interactions between molecules inside cells. The research in Membrane Computing has lead to very important theoretical results that show how, in principle, cells (...)
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  3. Cognitive Computation Sans Representation.Paul Schweizer - 2017 - In Thomas Powers (ed.), Philosophy and Computing: Essays in epistemology, philosophy of mind, logic, and ethics,. Cham, Switzerland: Springer. pp. 65-84.
    The Computational Theory of Mind (CTM) holds that cognitive processes are essentially computational, and hence computation provides the scientific key to explaining mentality. The Representational Theory of Mind (RTM) holds that representational content is the key feature in distinguishing mental from non-mental systems. I argue that there is a deep incompatibility between these two theoretical frameworks, and that the acceptance of CTM provides strong grounds for rejecting RTM. The focal point of the incompatibility is the fact that representational content (...)
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  4. Why Computers Are Not Intelligent: An Argument.Richard Oxenberg - 2017 - Political Animal Magazine.
    Computers can mimic human intelligence, sometimes quite impressively. This has led some to claim that, a.) computers can actually acquire intelligence, and/or, b.) the human mind may be thought of as a very sophisticated computer. In this paper I argue that neither of these inferences are sound. The human mind and computers, I argue, operate on radically different principles.
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  5. Cognition, Computing and Dynamic Systems.Mario Villalobos & Joe Dewhurst - 2016 - Límite. Revista Interdisciplinaria de Filosofía y Psicología 1.
    Traditionally, computational theory (CT) and dynamical systems theory (DST) have presented themselves as opposed and incompatible paradigms in cognitive science. There have been some efforts to reconcile these paradigms, mainly, by assimilating DST to CT at the expenses of its anti-representationalist commitments. In this paper, building on Piccinini’s mechanistic account of computation and the notion of functional closure, we explore an alternative conciliatory strategy. We try to assimilate CT to DST by dropping its representationalist commitments, and by inviting CT (...)
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  6. Morphological Computation: Nothing but Physical Computation.Marcin Miłkowski - 2018 - Entropy 10 (20):942.
    The purpose of this paper is to argue against the claim that morphological computation is substantially different from other kinds of physical computation. I show that some (but not all) purported cases of morphological computation do not count as specifically computational, and that those that do are solely physical computational systems. These latter cases are not, however, specific enough: all computational systems, not only morphological ones, may (and sometimes should) be studied in various ways, including their energy (...)
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  7. Computational Mechanisms and Models of Computation.Marcin Miłkowski - 2014 - Philosophia Scientiae 18:215-228.
    In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. -/- In this paper, I claim that mechanistic accounts of computation should allow for a broad (...)
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  8. Computing and Philosophy: Selected Papers From IACAP 2014.Vincent C. Müller (ed.) - 2016 - Springer.
    This volume offers very selected papers from the 2014 conference of the “International Association for Computing and Philosophy” (IACAP) - a conference tradition of 28 years. - - - Table of Contents - 0 Vincent C. Müller: - Editorial - 1) Philosophy of computing - 1 Çem Bozsahin: - What is a computational constraint? - 2 Joe Dewhurst: - Computing Mechanisms and Autopoietic Systems - 3 Vincenzo Fano, Pierluigi Graziani, Roberto Macrelli and Gino Tarozzi: - Are Gandy Machines really local? (...)
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  9. Computer-Assisted Argument Mapping: A Rationale Approach.Martin Davies - 2009 - Higher Education 58:799-820.
    Computer-Assisted Argument Mapping (CAAM) is a new way of understanding arguments. While still embryonic in its development and application, CAAM is being used increasingly as a training and development tool in the professions and government. Inroads are also being made in its application within education. CAAM claims to be helpful in an educational context, as a tool for students in responding to assessment tasks. However, to date there is little evidence from students that this is the case. This paper outlines (...)
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  10.  60
    Computational Modeling as a Philosophical Methodology.Patrick Grim - 2003 - In Luciano Floridi (ed.), The Blackwell Guide to the Philosophy of Computing and Information. Blackwell. pp. 337--349.
    Since the sixties, computational modeling has become increasingly important in both the physical and the social sciences, particularly in physics, theoretical biology, sociology, and economics. Sine the eighties, philosophers too have begun to apply computational modeling to questions in logic, epistemology, philosophy of science, philosophy of mind, philosophy of language, philosophy of biology, ethics, and social and political philosophy. This chapter analyzes a selection of interesting examples in some of those areas.
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  11. Computation of Higher Order Lie Derivatives on the Infinity Computer.Felice Iavernaro, Francesca Mazzia, Marat Mukhametzhanov & Yaroslav Sergeyev - 2021 - Journal of Computational and Applied Mathematics 383:113135.
    In this paper, we deal with the computation of Lie derivatives, which are required, for example, in some numerical methods for the solution of differential equations. One common way for computing them is to use symbolic computation. Computer algebra software, however, might fail if the function is complicated, and cannot be even performed if an explicit formulation of the function is not available, but we have only an algorithm for its computation. An alternative way to address the (...)
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  12. Cloud Computing and Big Data for Oil and Gas Industry Application in China.Yang Zhifeng, Feng Xuehui, Han Fei, Yuan Qi, Cao Zhen & Zhang Yidan - 2019 - Journal of Computers 1.
    The oil and gas industry is a complex data-driven industry with compute-intensive, data-intensive and business-intensive features. Cloud computing and big data have a broad application prospect in the oil and gas industry. This research aims to highlight the cloud computing and big data issues and challenges from the informatization in oil and gas industry. In this paper, the distributed cloud storage architecture and its applications for seismic data of oil and gas industry are focused on first. Then,cloud desktop for oil (...)
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  13. Cloud Computing and its Ethical Challenges.Matteo Turilli & Luciano Floridi - manuscript
    The paper analyses six ethical challenges posed by cloud computing, concerning ownership, safety, fairness, responsibility, accountability and privacy. The first part defines cloud computing on the basis of a resource-oriented approach, and outlines the main features that characterise such technology. Following these clarifications, the second part argues that cloud computing reshapes some classic problems often debated in information and computer ethics. To begin with, cloud computing makes possible a complete decoupling of ownership, possession and use of data and this helps (...)
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  14. Causality, Computing, and Complexity.Russ Abbott - 2015
    I discuss two categories of causal relationships: primitive causal interactions of the sort characterized by Phil Dowe and the more general manipulable causal relationships as defined by James Woodward. All primitive causal interactions are manipulable causal relationships, but there are manipulable causal relationships that are not primitive causal interactions. I’ll call the latter constructed causal relationships, and I’ll argue that constructed causal relationships serve as a foundation for both computing and complex systems. -/- Perhaps even more interesting are autonomous causal (...)
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  15. Computable Rationality, NUTS, and the Nuclear Leviathan.S. M. Amadae - 2018 - In Daniel Bessner & Nicolas Guilhot (eds.), The Decisionist Imagination: Democracy, Sovereignty and Social Science in the 20th Century. New York, NY, USA:
    This paper explores how the Leviathan that projects power through nuclear arms exercises a unique nuclearized sovereignty. In the case of nuclear superpowers, this sovereignty extends to wielding the power to destroy human civilization as we know it across the globe. Nuclearized sovereignty depends on a hybrid form of power encompassing human decision-makers in a hierarchical chain of command, and all of the technical and computerized functions necessary to maintain command and control at every moment of the sovereign's existence: this (...)
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  16.  24
    On Computable Numbers, Non-Universality, and the Genuine Power of Parallelism.Nancy Salay & Selim Akl - 2015 - International Journal of Unconventional Computing 11 (3-4):283-297.
    We present a simple example that disproves the universality principle. Unlike previous counter-examples to computational universality, it does not rely on extraneous phenomena, such as the availability of input variables that are time varying, computational complexity that changes with time or order of execution, physical variables that interact with each other, uncertain deadlines, or mathematical conditions among the variables that must be obeyed throughout the computation. In the most basic case of the new example, all that is used is (...)
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  17. Quantum Computer: Quantum Model and Reality.Vasil Penchev - 2020 - Epistemology eJournal (Elsevier: SSRN) 13 (17):1-7.
    Any computer can create a model of reality. The hypothesis that quantum computer can generate such a model designated as quantum, which coincides with the modeled reality, is discussed. Its reasons are the theorems about the absence of “hidden variables” in quantum mechanics. The quantum modeling requires the axiom of choice. The following conclusions are deduced from the hypothesis. A quantum model unlike a classical model can coincide with reality. Reality can be interpreted as a quantum computer. The physical processes (...)
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  18. Computational Entrepreneurship: From Economic Complexities to Interdisciplinary Research.Quan-Hoang Vuong - 2019 - Problems and Perspectives in Management 17 (1):117-129.
    The development of technology is unbelievably rapid. From limited local networks to high speed Internet, from crude computing machines to powerful semi-conductors, the world had changed drastically compared to just a few decades ago. In the constantly renewing process of adapting to such an unnaturally high-entropy setting, innovations as well as entirely new concepts, were often born. In the business world, one such phenomenon was the creation of a new type of entrepreneurship. This paper proposes a new academic discipline of (...)
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  19. Computing Mechanisms and Autopoietic Systems.Joe Dewhurst - 2016 - In Vincent Müller (ed.), Computing and Philosophy. Springer Verlag. pp. 17-26.
    This chapter draws an analogy between computing mechanisms and autopoietic systems, focusing on the non-representational status of both kinds of system (computational and autopoietic). It will be argued that the role played by input and output components in a computing mechanism closely resembles the relationship between an autopoietic system and its environment, and in this sense differs from the classical understanding of inputs and outputs. The analogy helps to make sense of why we should think of computing mechanisms as non-representational, (...)
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  20. Computer Simulations in Science and Engineering. Concept, Practices, Perspectives.Juan Manuel Durán - 2018 - Springer.
    This book addresses key conceptual issues relating to the modern scientific and engineering use of computer simulations. It analyses a broad set of questions, from the nature of computer simulations to their epistemological power, including the many scientific, social and ethics implications of using computer simulations. The book is written in an easily accessible narrative, one that weaves together philosophical questions and scientific technicalities. It will thus appeal equally to all academic scientists, engineers, and researchers in industry interested in questions (...)
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  21. Computers, Dynamical Systems, Phenomena, and the Mind.Marco Giunti - 1992 - Dissertation, Indiana University
    This work addresses a broad range of questions which belong to four fields: computation theory, general philosophy of science, philosophy of cognitive science, and philosophy of mind. Dynamical system theory provides the framework for a unified treatment of these questions. ;The main goal of this dissertation is to propose a new view of the aims and methods of cognitive science--the dynamical approach . According to this view, the object of cognitive science is a particular set of dynamical systems, which (...)
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  22. Learning Computer Networks Using Intelligent Tutoring System.Mones M. Al-Hanjori, Mohammed Z. Shaath & Samy S. Abu Naser - 2017 - International Journal of Advanced Research and Development 2 (1).
    Intelligent Tutoring Systems (ITS) has a wide influence on the exchange rate, education, health, training, and educational programs. In this paper we describe an intelligent tutoring system that helps student study computer networks. The current ITS provides intelligent presentation of educational content appropriate for students, such as the degree of knowledge, the desired level of detail, assessment, student level, and familiarity with the subject. Our Intelligent tutoring system was developed using ITSB authoring tool for building ITS. A preliminary evaluation of (...)
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  23. Computational Models (of Narrative) for Literary Studies.Antonio Lieto - 2015 - Semicerchio, Rivista di Poesia Comparata 2 (LIII):38-44.
    In the last decades a growing body of literature in Artificial Intelligence (AI) and Cognitive Science (CS) has approached the problem of narrative understanding by means of computational systems. Narrative, in fact, is an ubiquitous element in our everyday activity and the ability to generate and understand stories, and their structures, is a crucial cue of our intelligence. However, despite the fact that - from an historical standpoint - narrative (and narrative structures) have been an important topic of investigation in (...)
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  24.  90
    Computing, Modelling, and Scientific Practice: Foundational Analyses and Limitations.Philippos Papayannopoulos - 2018 - Dissertation,
    This dissertation examines aspects of the interplay between computing and scientific practice. The appropriate foundational framework for such an endeavour is rather real computability than the classical computability theory. This is so because physical sciences, engineering, and applied mathematics mostly employ functions defined in continuous domains. But, contrary to the case of computation over natural numbers, there is no universally accepted framework for real computation; rather, there are two incompatible approaches --computable analysis and BSS model--, both claiming to (...)
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  25. Computational Logic. Vol. 1: Classical Deductive Computing with Classical Logic. 2nd Ed.Luis M. Augusto - 2022 - London: College Publications.
    This is the 3rd edition. Although a number of new technological applications require classical deductive computation with non-classical logics, many key technologies still do well—or exclusively, for that matter—with classical logic. In this first volume, we elaborate on classical deductive computing with classical logic. The objective of the main text is to provide the reader with a thorough elaboration on both classical computing – a.k.a. formal languages and automata theory – and classical deduction with the classical first-order predicate calculus (...)
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  26.  52
    Integrating Computer Vision Algorithms and Ontologies for Spectator Crowd Behavior Analysis.Davide Conigliaro, Celine Hudelot, Roberta Ferrario & Daniele Porello - 2017 - In Vittorio Murino, Marco Cristani, Shishir Shah & Silvio Savarese (eds.), Group and Crowd Behavior for Computer Vision, 1st Edition. pp. 297-319.
    In this paper, building on these previous works, we propose to go deeper into the understanding of crowd behavior by proposing an approach which integrates ontologi- cal models of crowd behavior and dedicated computer vision algorithms, with the aim of recognizing some targeted complex events happening in the playground from the observation of the spectator crowd behavior. In order to do that, we first propose an ontology encoding available knowledge on spectator crowd behavior, built as a spe- cialization of the (...)
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  27.  41
    A Computational Model of Affects.Mika Turkia - 2009 - In D. Dietrich, G. Fodor, G. Zucker & D. Bruckner (eds.), Simulating the mind: A technical neuropsychoanalytical approach. pp. 277-289.
    Emotions and feelings (i.e. affects) are a central feature of human behavior. Due to complexity and interdisciplinarity of affective phenomena, attempts to define them have often been unsatisfactory. This article provides a simple logical structure, in which affective concepts can be defined. The set of affects defined is similar to the set of emotions covered in the OCC model, but the model presented in this article is fully computationally defined, whereas the OCC model depends on undefined concepts. Following Matthis, affects (...)
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  28. Computing Nature.Gordana Dodig-Crncovic & Raffaela Giovagnoli - 2013 - Springer.
    The articles in this volume present a selection of works from the Symposium on Natu-ral/Unconventional Computing at AISB/IACAP (British Society for the Study of Artificial Intelligence and the Simulation of Behaviour and The International Association for Computing and Philosophy) World Congress 2012, held at the University of Birmingham, celebrating Turing centenary. This book is about nature considered as the totality of physical existence, the universe. By physical we mean all phenomena - objects and processes - that are possible to detect (...)
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  29.  10
    Info-Computational Constructivism and Cognition.G. Dodig-Crnkovic - 2014 - Constructivist Foundations 9 (2):223-231.
    Context: At present, we lack a common understanding of both the process of cognition in living organisms and the construction of knowledge in embodied, embedded cognizing agents in general, including future artifactual cognitive agents under development, such as cognitive robots and softbots. Purpose: This paper aims to show how the info-computational approach (IC) can reinforce constructivist ideas about the nature of cognition and knowledge and, conversely, how constructivist insights (such as that the process of cognition is the process of life) (...)
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  30.  63
    Computer Simulation of Human Thinking: An Inquiry Into its Possibility and Implications.Napoleon Mabaquiao Jr - 2011 - Philosophia 40 (1):76-87.
    Critical in the computationalist account of the mind is the phenomenon called computational or computer simulation of human thinking, which is used to establish the theses that human thinking is a computational process and that computing machines are thinking systems. Accordingly, if human thinking can be simulated computationally then human thinking is a computational process; and if human thinking is a computational process then its computational simulation is itself a thinking process. This paper shows that the said phenomenon—the computational simulation (...)
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  31. The Computable Universe: From Prespace Metaphysics to Discrete Quantum Mechanics.Martin Leckey - 1997 - Dissertation, Monash University
    The central motivating idea behind the development of this work is the concept of prespace, a hypothetical structure that is postulated by some physicists to underlie the fabric of space or space-time. I consider how such a structure could relate to space and space-time, and the rest of reality as we know it, and the implications of the existence of this structure for quantum theory. Understanding how this structure could relate to space and to the rest of reality requires, I (...)
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  32. Extended Computation: Wide Computationalism in Reverse.Paul Smart, Wendy Hall & Michael Boniface - 2021 - Proceedings of the 13th ACM Web Science Conference (Companion Volume).
    Arguments for extended cognition and the extended mind are typically directed at human-centred forms of cognitive extension—forms of cognitive extension in which the cognitive/mental states/processes of a given human individual are subject to a form of extended or wide realization. The same is true of debates and discussions pertaining to the possibility of Web-extended minds and Internet-based forms of cognitive extension. In this case, the focus of attention concerns the extent to which the informational and technological elements of the online (...)
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  33.  64
    Computing Machinery and Sexual Difference: The Sexed Presuppositions Underlying the Turing Test.Amy Kind - forthcoming - In Jennifer McWeeny & Keya Maitra (eds.), Feminist Philosophy of Mind.
    In his 1950 paper “Computing Machinery and Intelligence,” Alan Turing proposed that we can determine whether a machine thinks by considering whether it can win at a simple imitation game. A neutral questioner communicates with two different systems – one a machine and a human being – without knowing which is which. If after some reasonable amount of time the machine is able to fool the questioner into identifying it as the human, the machine wins the game, and we should (...)
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  34. Computer Models and the Evidence of Anthropogenic Climate Change: An Epistemology of Variety-of-Evidence Inferences and Robustness Analysis.Martin Vezer - 2016 - Computer Models and the Evidence of Anthropogenic Climate Change: An Epistemology of Variety-of-Evidence Inferences and Robustness Analysis MA Vezér Studies in History and Philosophy of Science 56:95-102.
    To study climate change, scientists employ computer models, which approximate target systems with various levels of skill. Given the imperfection of climate models, how do scientists use simulations to generate knowledge about the causes of observed climate change? Addressing a similar question in the context of biological modelling, Levins (1966) proposed an account grounded in robustness analysis. Recent philosophical discussions dispute the confirmatory power of robustness, raising the question of how the results of computer modelling studies contribute to the body (...)
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  35. Computation on Information, Meaning and Representations. An Evolutionary Approach (World Scientific 2011).Christophe Menant - 2011 - In Dodig-Crnkovic, Gordana & Mark Burgin (eds.), Information and Computation. World Scientific. pp. 255-286.
    Understanding computation as “a process of the dynamic change of information” brings to look at the different types of computation and information. Computation of information does not exist alone by itself but is to be considered as part of a system that uses it for some given purpose. Information can be meaningless like a thunderstorm noise, it can be meaningful like an alert signal, or like the representation of a desired food. A thunderstorm noise participates to the (...)
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  36. 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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  37. Information, Computation, Cognition. Agency-Based Hierarchies of Levels.Gordana Dodig-Crnkovic - 2016 - In Vincent Müller (ed.), Fundamental Issues of Artificial Intelligence. Zurich: Springer. pp. 139-159.
    This paper connects information with computation and cognition via concept of agents that appear at variety of levels of organization of physical/chemical/cognitive systems – from elementary particles to atoms, molecules, life-like chemical systems, to cognitive systems starting with living cells, up to organisms and ecologies. In order to obtain this generalized framework, concepts of information, computation and cognition are generalized. In this framework, nature can be seen as informational structure with computational dynamics, where an (info-computational) agent is needed (...)
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  38. Computability. Computable Functions, Logic, and the Foundations of Mathematics. [REVIEW]R. Zach - 2002 - History and Philosophy of Logic 23 (1):67-69.
    Epstein and Carnielli's fine textbook on logic and computability is now in its second edition. The readers of this journal might be particularly interested in the timeline `Computability and Undecidability' added in this edition, and the included wall-poster of the same title. The text itself, however, has some aspects which are worth commenting on.
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  39. Physical Computation: A Mechanistic Account. [REVIEW]Joe Dewhurst - 2016 - Philosophical Psychology 29 (5):795-797.
    Physical Computation is the summation of Piccinini’s work on computation and mechanistic explanation over the past decade. It draws together material from papers published during that time, but also provides additional clarifications and restructuring that make this the definitive presentation of his mechanistic account of physical computation. This review will first give a brief summary of the account that Piccinini defends, followed by a chapter-by-chapter overview of the book, before finally discussing one aspect of the account in (...)
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  40. A Computational Theory of Perspective and Reference in Narrative.Janyce M. Wiebe & William J. Rapaport - 1988 - In Proceedings of the 26th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. pp. 131-138.
    Narrative passages told from a character's perspective convey the character's thoughts and perceptions. We present a discourse process that recognizes characters'.
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  41. The Computational Modeling of Inferential and Referential Competence.Fabrizio Calzavarini & Antonio Lieto - 2018 - In AISC 2018 Proceedings.
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  42. Using Computer-Assisted Argument Mapping to Teach Reasoning to Students.Martin Davies, Ashley Barnett & Tim van Gelder - 2021 - In J. Anthony Blair (ed.), Studies in Critical Thinking (2nd Edition). Windsor, ON, Canada: Windsor Studies in Argumentation. pp. 115-152.
    Argument mapping is a way of diagramming the logical structure of an argument to explicitly and concisely represent reasoning. The use of argument mapping in critical thinking instruction has increased dramatically in recent decades. This paper overviews the innovation and provides a procedural approach for new teaches wanting to use argument mapping in the classroom. A brief history of argument mapping is provided at the end of this paper.
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  43. Computer Simulation and the Features of Novel Empirical Data.Greg Lusk - 2016 - Studies in History and Philosophy of Science Part A 56:145-152.
    In an attempt to determine the epistemic status of computer simulation results, philosophers of science have recently explored the similarities and differences between computer simulations and experiments. One question that arises is whether and, if so, when, simulation results constitute novel empirical data. It is often supposed that computer simulation results could never be empirical or novel because simulations never interact with their targets, and cannot go beyond their programming. This paper argues against this position by examining whether, and under (...)
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  44.  12
    COMPUTATIONAL TREATMENT FOR LIFE SCIENCE.Igor F. Mikhailov - 2021 - Vestnik Tomskogo Gosudarstvennogo Universiteta. Filosofiya, Sotsiologiya, Politologiya 1 (61):38-46.
    According to some critics, if biology is a kind of reverse engineering for the nature, it is quite poorly prepared for the task. Thus, the issue is more likely with its ontology. Multiple hypotheses and conjectures found in papers on methodological issues claim that living systems should be viewed as complex networks of signal-transmitting paths, both neural and non-neural, that feature modularity and feedback circuits and are prone to emergent properties and increasing complexity. If so, we are on the eve (...)
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  45. Computation and Multiple Realizability.Marcin Miłkowski - 2016 - In Vincent Müller (ed.), Fundamental Issues of Artificial Intelligence. Springer. pp. 29-41.
    Multiple realizability (MR) is traditionally conceived of as the feature of computational systems, and has been used to argue for irreducibility of higher-level theories. I will show that there are several ways a computational system may be seen to display MR. These ways correspond to (at least) five ways one can conceive of the function of the physical computational system. However, they do not match common intuitions about MR. I show that MR is deeply interest-related, and for this reason, difficult (...)
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  46.  89
    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 (...)
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  47.  38
    Computer-Administered Testing Practice in Higher Education in Era of Severe Acute Respiratory Syndrome-Related Diseases Outbreaks.Valentine Joseph Owan - 2020 - In V. C. Emeribe, L. U. Akah, O. A. DadA, D. A. Alawa & B. A. Akuegwu (eds.), Multidisciplinary issues in health, human kinetics and general education practices. Calabar, Nigeria: University of Calabar Press. pp. 429-442.
    The focal point of this chapter is to discuss the concept of computer regulated testing and its implications in an era of Severe Acute Respiratory Syndrome (SARS) related infection pandemics. This is especially significant because during the outbreak of most SARS-related diseases (like the COVID-19), social and physical distancing is advocated by the government of different nations. SARS-related diseases are caused by a virus known as the coronavirus which affects the respiration of infected persons or animals. These diseases can be (...)
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  48.  48
    Computational Complexity in the Philosophy of Mind: Unconventional Methods to Solve the Problem of Logical Omniscience.Safal Aryal - manuscript
    The philosophy of mind is traditionally concerned with the study of mental processes, language, the representation of knowledge and the relation of the mind shares with the body; computational complexity theory is related to the classification of computationally solvable problems (be it via execution time, storage requirements, etc...). While there are well-established links between computer science in general & the philosophy of mind, many possible solutions to traditional problems in the philosophy of mind have not yet been analyzed from the (...)
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  49.  10
    Computing with Causal Theories.Erkan Tin & Varol Akman - 1992 - International Journal of Pattern Recognition and Artificial Intelligence 6 (4):699-730.
    Formalizing commonsense knowledge for reasoning about time has long been a central issue in AI. It has been recognized that the existing formalisms do not provide satisfactory solutions to some fundamental problems, viz. the frame problem. Moreover, it has turned out that the inferences drawn do not always coincide with those one had intended when one wrote the axioms. These issues call for a well-defined formalism and useful computational utilities for reasoning about time and change. Yoav Shoham of Stanford University (...)
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  50.  92
    Computational Situation Theory.Erkan Tin & Varol Akman - 1994 - ACM SIGART Bulletin 5 (4):4-17.
    Situation theory has been developed over the last decade and various versions of the theory have been applied to a number of linguistic issues. However, not much work has been done in regard to its computational aspects. In this paper, we review the existing approaches towards 'computational situation theory' with considerable emphasis on our own research.
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