Search results for 'Computing' (try it on Scholar)

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  1. Matteo Colombo (2016). Why Build a Virtual Brain? Large-Scale Neural Simulations as Jump Start for Cognitive Computing. Journal of Experimental and Theoretical Artificial Intelligence.
    Despite the impressive amount of financial resources recently invested in carrying out large-scale brain simulations, it is controversial what the pay-offs are of pursuing this project. One idea is that from designing, building, and running a large-scale neural simulation, scientists acquire knowledge about the computational performance of the simulating system, rather than about the neurobiological system represented in the simulation. It has been claimed that this knowledge may usher in a new era of neuromorphic, cognitive computing systems. This study (...)
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  2.  79
    Vincent C. Müller (2008). What a Course on Philosophy of Computing is Not. APA Newsletter on Philosophy and Computers 8 (1):36-38.
    Immanuel Kant famously defined philosophy to be about three questions: “What can I know? What should I do? What can I hope for?” (KrV, B833). I want to suggest that the three questions of our course on the philosophy of computing are: What is computing? What should we do with computing? What could computing do?
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  3.  23
    Viola Schiaffonati & Mario Verdicchio (2014). Computing and Experiments. Philosophy and Technology 27 (3):359-376.
    The question about the scientific nature of computing has been widely debated with no universal consensus reached about its disciplinary status. Positions vary from acknowledging computing as the science of computers to defining it as a synthetic engineering discipline. In this paper, we aim at discussing the nature of computing from a methodological perspective. We consider, in particular, the nature and role of experiments in this field, whether they can be considered close to the traditional experimental scientific (...)
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  4.  17
    Boudewijn de Bruin & Luciano Floridi (forthcoming). The Ethics of Cloud Computing. Science and Engineering Ethics:1-19.
    Cloud computing is rapidly gaining traction in business. It offers businesses online services on demand and allows them to cut costs on hardware and IT support. This is the first paper in business ethics dealing with this new technology. It analyzes the informational duties of hosting companies that own and operate cloud computing datacentres. It considers the cloud services providers leasing ‘space in the cloud’ from hosting companies. And it examines the business and private ‘clouders’ using these services. (...)
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  5.  60
    Liesbeth De Mol & Giuseppe Primiero (2014). Facing Computing as Technique: Towards a History and Philosophy of Computing. Philosophy and Technology 27 (3):321-326.
    We present the methodological principles underlying the scientific activities of the DHST Commission on the History and Philosophy of Computing. This volume collects refereed selected papers from the First International Conference organized by the Commission.
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  6.  45
    Matti Tedre (2011). Computing as a Science: A Survey of Competing Viewpoints. [REVIEW] Minds and Machines 21 (3):361-387.
    Since the birth of computing as an academic discipline, the disciplinary identity of computing has been debated fiercely. The most heated question has concerned the scientific status of computing. Some consider computing to be a natural science and some consider it to be an experimental science. Others argue that computing is bad science, whereas some say that computing is not a science at all. This survey article presents viewpoints for and against computing as (...)
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  7.  7
    Viola Schiaffonati (2016). Stretching the Traditional Notion of Experiment in Computing: Explorative Experiments. Science and Engineering Ethics 22 (3):647-665.
    Experimentation represents today a ‘hot’ topic in computing. If experiments made with the support of computers, such as computer simulations, have received increasing attention from philosophers of science and technology, questions such as “what does it mean to do experiments in computer science and engineering and what are their benefits?” emerged only recently as central in the debate over the disciplinary status of the discipline. In this work we aim at showing, also by means of paradigmatic examples, how the (...)
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  8.  7
    Eric Hatleback & Jonathan M. Spring (2014). Exploring a Mechanistic Approach to Experimentation in Computing. Philosophy and Technology 27 (3):441-459.
    The mechanistic approach in philosophy of science contributes to our understanding of experimental design. Applying the mechanistic approach to experimentation in computing is beneficial for two reasons. It connects the methodology of experimentation in computing with the methodology of experimentation in established sciences, thereby strengthening the scientific reputability of computing and the quality of experimental design therein. Furthermore, it pinpoints the idiosyncrasies of experimentation in computing: computing deals closely with both natural and engineered mechanisms. Better (...)
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  9.  23
    Soraj Hongladarom (2013). Ubiquitous Computing, Empathy and the Self. AI and Society 28 (2):227-236.
    The paper discusses ubiquitous computing and the conception of the self, especially the question how the self should be understood in the environment pervaded by ubiquitous computing, and how ubiquitous computing makes possible direct empathy where each person or self connected through the network has direct access to others’ thoughts and feelings. Starting from a conception of self, which is essentially distributed, composite and constituted through information, the paper argues that when a number of selves are connected (...)
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  10.  34
    Bernard Gert (1999). Common Morality and Computing. Ethics and Information Technology 1 (1):53-60.
    This article shows how common morality can be helpful in clarifying the discussion of ethical issues that arise in computing. Since common morality does not always provide unique answers to moral questions, not all such issues can be resolved, however common morality does provide a clear answer to the question whether one can illegally copy software for a friend.
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  11.  9
    Robert Rosenberger (2013). The Importance of Generalized Bodily Habits for a Future World of Ubiquitous Computing. AI and Society 28 (3):289-296.
    In a future world of ubiquitous computing, in which humans interact with computerized technologies even more frequently and in even more situations than today, interface design will have increased importance. One feature of interface that I argue will be especially relevant is what I call abstract relational strategies. This refers to an approach (in both a bodily and conceptual sense) toward the use of a technology, an approach that is general enough to be applied in many different concrete scenarios. (...)
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  12.  41
    Rodney Van Meter (2014). Quantum Computing's Classical Problem, Classical Computing's Quantum Problem. Foundations of Physics 44 (8):819-828.
    Tasked with the challenge to build better and better computers, quantum computing and classical computing face the same conundrum: the success of classical computing systems. Small quantum computing systems have been demonstrated, and intermediate-scale systems are on the horizon, capable of calculating numeric results or simulating physical systems far beyond what humans can do by hand. However, to be commercially viable, they must surpass what our wildly successful, highly advanced classical computers can already do. At the (...)
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  13.  30
    Edward J. O'Boyle (2002). An Ethical Decision-Making Process for Computing Professionals. Ethics and Information Technology 4 (4):267-277.
    Our comments focus on the ACMCode of Ethics and situate the Code within ageneral ethical decision-making process tospecify the five steps which logically precedehuman action in ethical matters and determinethat action, and the individual differencetraits in these five steps which bear upon theresolution of an ethical problem and lead tomorally responsible action. Our main purpose isto present a cognitive moral processing modelwhich computing professionals can use to betterunderstand their professional rights andduties. It is clear that the Code providessubstantial guidance (...)
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  14.  19
    Uri Pincas (2011). Program Verification and Functioning of Operative Computing Revisited: How About Mathematics Engineering? [REVIEW] Minds and Machines 21 (2):337-359.
    The issue of proper functioning of operative computing and the utility of program verification, both in general and of specific methods, has been discussed a lot. In many of those discussions, attempts have been made to take mathematics as a model of knowledge and certitude achieving, and accordingly infer about the suitable ways to handle computing. I shortly review three approaches to the subject, and then take a stance by considering social factors which affect the epistemic status of (...)
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  15.  14
    Bernardo Aguilera (2015). Behavioural Explanation in the Realm of Non-Mental Computing Agents. Minds and Machines 25 (1):37-56.
    Recently, many philosophers have been inclined to ascribe mentality to animals on the main grounds that they possess certain complex computational abilities. In this paper I contend that this view is misleading, since it wrongly assumes that those computational abilities demand a psychological explanation. On the contrary, they can be just characterised from a computational level of explanation, which picks up a domain of computation and information processing that is common to many computing systems but is autonomous from the (...)
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  16.  28
    Lukáš Sekanina (2007). Evolved Computing Devices and the Implementation Problem. Minds and Machines 17 (3):311-329.
    The evolutionary circuit design is an approach allowing engineers to realize computational devices. The evolved computational devices represent a distinctive class of devices that exhibits a specific combination of properties, not visible and studied in the scope of all computational devices up till now. Devices that belong to this class show the required behavior; however, in general, we do not understand how and why they perform the required computation. The reason is that the evolution can utilize, in addition to the (...)
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  17.  15
    James H. Fetzer (2000). Computing is at Best a Special Kind of Thinking. In The Proceedings of the Twentieth World Congress of Philosophy. Charlottesville: Philosophy Doc Ctr 103-113.
    When computing is defined as the causal implementation of algorithms and algorithms are defined as effective decision procedures, human thought is mental computation only if it is governed by mental algorithms. An examination of ordinary thinking, however, suggests that most human thought processes are non-algorithmic. Digital machines, moreover, are mark-manipulating or string-processing systems whose marks or strings do not stand for anything for those systems, while minds are semiotic (or “signusing”) systems for which signs stand for other things for (...)
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  18.  3
    Geoffrey K. Pullum (1987). Natural Language Interfaces and Strategic Computing. AI and Society 1 (1):47-58.
    Modern weaponry is often too complex for unaided human operation, and is largely or totally controlled by computers. But modern software, particularly artificial intelligence software, exhibits such complexity and inscrutability that there are grave dangers associated with its use in non-benign applications. Recent efforts to make computer systems more accessible to military personnel through natural language processing systems, as proposed in the Strategic Computing Initiative of the Defense Advanced Research Projects Agency, increases rather than decreases the dangers of unpredictable (...)
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  19.  6
    Chris Hables Gray (1988). The Strategic Computing Program at Four Years: Implications and Intimations. [REVIEW] AI and Society 2 (2):141-149.
    Examining the Strategic Computing Program after four years, in the context of the crucial recognition that it is only a small part of the whole range of military artificial intelligence applications, suggests a number of clear implications and intimations about such crucial questions as: 1) the current roles of industry and the universities in developing high technology war; 2) the effects on political and military policy of high-tech weapons systems; and 3) the importance of advanced military computing to (...)
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  20.  5
    Joanna Berzowska (2006). Personal Technologies: Memory and Intimacy Through Physical Computing. [REVIEW] AI and Society 20 (4):446-461.
    In this paper, I present an overview of personal and intimate technologies within a pedagogical context. I describe two courses that I have developed for Computation Arts at Concordia University: “Tangible Media and Physical Computing” and “Second Skin and Soft Wear.” Each course deals with different aspects of physical computing and tangible media in a Fine Arts context. In both courses, I introduce concepts of soft computation and intimate reactive artifacts as artworks. I emphasize the concept of memory (...)
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  21.  4
    Joan Truckenbrod (1993). Women and the Social Construction of the Computing Culture: Evolving New Forms of Computing. [REVIEW] AI and Society 7 (4):345-357.
    Women have been excluded from the mainstream development of computer hardware and software. Consequently there is an imbalance in the masculine and feminine characteristics, functioning and applications of computing. A masculine approach is encoded into the technical personality of computing, and in the skills and knowledge necessary to utilise computers. The feminine perspective broadens the scope and objectives of computing. This paper examines the current computing culture, and proposes new models for computing that embrace the (...)
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  22.  4
    Lauri Forsman (1998). Proactive Management of Distributed Organisational Computing: Prevention Always Pays, Doesn't It? [REVIEW] AI and Society 12 (4):328-345.
    Organisations have eagerly adopted the new opportunities provided by distributed computing technology. These opportunities have also created new dependency on the technology and threats of technical problems. Information technology (IT) management has to choose its position towards these new technical risks. Should the problems be prevented proactively in advance or settled reactively afterwards?This paper draws conclusions from an action research case study aimed at proactive versus reactive end-user support. Between 1994 and 1997 one of the business units in Nokia (...)
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  23.  5
    Chris Boyne (1994). Notes Towards a Definition of Human-Centred Computing. AI and Society 8 (1):60-70.
    Current usage of the expression “human-centred” in computing contexts suffers from a lack of clarity, and involves internal contradictions. It is not enough to base the concept of human-centredness on ideas of social utility, collaborative working or human controllability. However, the concept of human action (which embodies reference to human freedom) provides a theoretical underpinning to human-centredness by combining, from a human standpoint, concern with process and concern with goals. This has consequences for the design process, prompting us to (...)
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  24.  52
    Vincent C. Müller (ed.) (2016). Computing and Philosophy: Selected Papers From IACAP 2014. 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 (...)
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  25. James H. Moor (1999). Just Consequentialism and Computing. Ethics and Information Technology 1 (1):61-65.
    Computer and information ethics, as well as other fields of applied ethics, need ethical theories which coherently unify deontological and consequentialist aspects of ethical analysis. The proposed theory of just consequentialism emphasizes consequences of policies within the constraints of justice. This makes just consequentialism a practical and theoretically sound approach to ethical problems of computer and information ethics.
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  26.  78
    Włodzisław Duch (2005). Brain-Inspired Conscious Computing Architecture. Journal of Mind and Behavior 26 (1-2):1-21.
    What type of artificial systems will claim to be conscious and will claim to experience qualia? The ability to comment upon physical states of a brain-like dynamical system coupled with its environment seems to be sufficient to make claims. The flow of internal states in such system, guided and limited by associative memory, is similar to the stream of consciousness. Minimal requirements for an artificial system that will claim to be conscious were given in form of specific architecture named articon. (...)
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  27.  1
    Jenifer S. Winter (2008). Emerging Policy Problems Related to Ubiquitous Computing: Negotiating Stakeholders’ Visions of the Future. Knowledge, Technology and Policy 21 (4):191-203.
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  28.  41
    Anthony F. Beavers (2001). Luciano Floridi, Philosophy and Computing: An Introduction. [REVIEW] Ethics and Information Technology 3 (4):299-301.
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  29.  15
    Joseph S. Fulda (2000). A Gift of Fire: Social Legal, and Ethical Issues in Computing by Sara Baase. [REVIEW] Ethics and Information Technology 2 (4):241-247.
    Extremely favorable review, with hardly any criticisms at all.
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  30.  6
    Anand Ranganathan & Roy H. Campbell (2007). What is the Complexity of a Distributed Computing System? Complexity 12 (6):37-45.
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  31.  7
    Marian Verkerk (1999). Ethics, Computing and Medicine. Informatics and the Transformation of Health Care. Kenneth W. Goodman, Editor. Ethics and Information Technology 1 (4):303-304.
  32.  5
    Foerster H. Von & A. Müller (2008). Computing a Reality. Heinz von Foerster's Lecture at the A.U.M Conference in 1973. Edited by Albert Müller. Constructivist Foundations 4 (1).
    Purpose: Commenting on the transcript of a lecture. Findings: The document reconstructs the development of the original 1973 lecture by Heinz von Foerster into his best-known paper, On Constructing a Reality. Many aspects of that paper can be identified as being shaped through interaction with the audience. Implications: The lecture documented here was a forerunner of a central paper in constructivism.
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  33.  4
    J. D. Weinland & W. S. Schlauch (1937). An Examination of the Computing Ability of Mr. Salo Finkelstein. Journal of Experimental Psychology 21 (4):382.
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  34.  10
    Lorenzo Magnai (2000). Philosophy and Computing. An Introduction, Luciano Floridi. Ethics and Information Technology 2 (2):137-138.
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  35. Joe Dewhurst (2016). Computing Mechanisms and Autopoietic Systems. In Vincent Müller (ed.), Computing and Philosophy. Springer International Publishing 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 (...)
     
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  36. Jacqueline G. Ord (1995). The Ethics of NHS Computing: A Terminal Case. [REVIEW] AI and Society 9 (1):80-90.
    Value in the British National Health Service have shifted away from patient care towards financial control. However, in the quest for efficiency , huge amounts of NHS money have been wasted on computer system which failed. In this paper, I draw on a case study to explore some of the ethical issues which underlie this kind of waste of resources. Issues include the gap between public pronouncements and personal experience, the chaos of which lies behind the facade of rationality, and (...)
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  37.  91
    Gualtiero Piccinini (2007). Computing Mechanisms. Philosophy of Science 74 (4):501-526.
    This paper offers an account of what it is for a physical system to be a computing mechanism—a system that performs computations. A computing mechanism is a mechanism whose function is to generate output strings from input strings and (possibly) internal states, in accordance with a general rule that applies to all relevant strings and depends on the input strings and (possibly) internal states for its application. This account is motivated by reasons endogenous to the philosophy of (...), namely, doing justice to the practices of computer scientists and computability theorists. It is also an application of recent literature on mechanisms, because it assimilates computational explanation to mechanistic explanation. The account can be used to individuate computing mechanisms and the functions they compute and to taxonomize computing mechanisms based on their computing power. (shrink)
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  38. Hong Liu, Bin Hu & Philip Moore (2015). HCI Model with Learning Mechanism for Cooperative Design in Pervasive Computing Environment. Journal of Internet Technology 16.
    This paper presents a human-computer interaction model with a three layers learning mechanism in a pervasive environment. We begin with a discussion around a number of important issues related to human-computer interaction followed by a description of the architecture for a multi-agent cooperative design system for pervasive computing environment. We present our proposed three- layer HCI model and introduce the group formation algorithm, which is predicated on a dynamic sharing niche technology. Finally, we explore the cooperative reinforcement learning and (...)
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  39.  31
    L. Floridi (ed.) (2004). The Blackwell Guide to the Philosophy of Computing and Information. Blackwell.
    This Guide provides an ambitious state-of-the-art survey of the fundamental themes, problems, arguments and theories constituting the philosophy of computing.
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  40.  20
    Luciano Floridi (1999). Philosophy and Computing: An Introduction. Routledge.
    This accessible book explores the development, history and future of Information and Communication Technology using examples from philosophy. Luciano Floridi offers both an introduction to these technologies and a philosophical analysis of the problems they pose. The book examines a wide range of areas of technology, including the digital revolution, the Web and Internet, Artificial Intelligence and CD-ROMS. We see how the relationship between philosophy and computing provokes many crucial philosophical questions. Ultimately, Philosophy and Computing outlines what the (...)
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  41.  13
    Bruno J. Strasser (2010). Collecting, Comparing, and Computing Sequences: The Making of Margaret O. Dayhoff's "Atlas of Protein Sequence and Structure", 1954–1965. [REVIEW] Journal of the History of Biology 43 (4):623 - 660.
    Collecting, comparing, and computing molecular sequences are among the most prevalent practices in contemporary biological research. They represent a specific way of producing knowledge. This paper explores the historical development of these practices, focusing on the work of Margaret O. Dayhoff, Richard V. Eck, and Robert S. Ledley, who produced the first computer-based collection of protein sequences, published in book format in 1965 as the Atlas of Protein Sequence and Structure. While these practices are generally associated with the rise (...)
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  42.  81
    Zenon W. Pylyshyn (1989). Computing and Cognitive Science. In Michael I. Posner (ed.), Foundations of Cognitive Science. MIT Press
    influence. One of the principal characteristics that distinguishes Cognitive Science from more traditional studies of cognition within Psychology, is the extent to which it has been influenced by both the ideas and the techniques of computing. It may come as a surprise to the outsider, then, to discover that there is no unanimity within the discipline on either (a) the nature (and in some cases the desireabilty) of the influence and (b) what computing is –- or at least (...)
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  43. Hava T. Siegelmann (2003). Neural and Super-Turing Computing. Minds and Machines 13 (1):103-114.
    ``Neural computing'' is a research field based on perceiving the human brain as an information system. This system reads its input continuously via the different senses, encodes data into various biophysical variables such as membrane potentials or neural firing rates, stores information using different kinds of memories (e.g., short-term memory, long-term memory, associative memory), performs some operations called ``computation'', and outputs onto various channels, including motor control commands, decisions, thoughts, and feelings. We show a natural model of neural (...) that gives rise to hyper-computation. Rigorous mathematical analysis is applied, explicating our model's exact computational power and how it changes with the change of parameters. Our analog neural network allows for supra-Turing power while keeping track of computational constraints, and thus embeds a possible answer to the superiority of the biological intelligence within the framework of classical computer science. We further propose it as standard in the field of analog computation, functioning in a role similar to that of the universal Turing machine in digital computation. In particular an analog of the Church-Turing thesis of digital computation is stated where the neural network takes place of the Turing machine. (shrink)
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  44.  84
    Patrick Grüneberg & Kenji Suzuki (2013). A Lesson From Subjective Computing: Autonomous Self-Referentiality and Social Interaction as Conditions for Subjectivity. AISB Proceedings 2012:18-28.
    In this paper, we model a relational notion of subjectivity by means of two experiments in subjective computing. The goal is to determine to what extent a cognitive and social robot can be regarded to act subjectively. The system was implemented as a reinforcement learning agent with a coaching function. To analyze the robotic agent we used the method of levels of abstraction in order to analyze the agent at four levels of abstraction. At one level the agent is (...)
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  45.  26
    James A. Stieb (2008). A Critique of Positive Responsibility in Computing. Science and Engineering Ethics 14 (2):219-233.
    It has been claimed that (1) computer professionals should be held responsible for an undisclosed list of “undesirable events” associated with their work and (2) most if not all computer disasters can be avoided by truly understanding responsibility. Programmers, software developers, and other computer professionals should be defended against such vague, counterproductive, and impossible ideals because these imply the mandatory satisfaction of social needs and the equation of ethics with a kind of altruism. The concept of social needs is debatable (...)
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  46. Gordana Dodig-Crncovic & Raffaela Giovagnoli (2013). Computing Nature. 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 (...)
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  47. R. C. Paton, H. S. Nwana, M. J. R. Shave & T. J. M. Bench-Capon (1994). An Examination of Some Metaphorical Contexts for Biologically Motivated Computing. British Journal for the Philosophy of Science 45 (2):505-525.
    Biologically motivated computing seeks to transfer ideas from the biosciences to computer science. In seeking to make transfers it is helpful to be able to appreciate the metaphors which people use. This is because metaphors provide the context through which analogies and similes are made and by which many scientific models are constructed. As such, it is important for any rapidly evolving domain of knowledge to have developments accounted for in these terms. This paper seeks to provide one overview (...)
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  48.  1
    Robert I. Soare (2009). Turing Oracle Machines, Online Computing, and Three Displacements in Computability Theory. Annals of Pure and Applied Logic 160 (3):368-399.
    We begin with the history of the discovery of computability in the 1930’s, the roles of Gödel, Church, and Turing, and the formalisms of recursive functions and Turing automatic machines . To whom did Gödel credit the definition of a computable function? We present Turing’s notion [1939, §4] of an oracle machine and Post’s development of it in [1944, §11], [1948], and finally Kleene-Post [1954] into its present form. A number of topics arose from Turing functionals including continuous functionals on (...)
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  49.  2
    Hector Zenil (2013). A Behavioural Foundation for Natural Computing and a Programmability Test. In Gordana Dodig-Crnkovic Raffaela Giovagnoli (ed.), Computing Nature. 87--113.
  50. John G. Cramer, Decryption and Quantum Computing: Seven Qubits and Counting.
    Alternate View Column AV-112 Keywords: quantum mechanics entangled states computer computing 7 qubits prime number factoring Schor algorithm NMR nuclear magnetic resonance fast parallel decryption coherence wave-function collapse many-worlds transactional interpretation Published in the June-2002 issue of Analog Science Fiction & Fact Magazine ; This column was written and submitted 12/19/2001 and is copyrighted ©2001 by John G. Cramer.
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