Search results for 'Artificial intelligence Philosophy' (try it on Scholar)

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  1. Morton Wagman (ed.) (2000). Historical Dictionary of Quotations in Cognitive Science: A Treasury of Quotations in Psychology, Philosophy, and Artificial Intelligence. Greenwood Press.score: 174.0
    Focuses on distinguished quotations representing the best thinking in philosophy, psychology, and artificial intelligence from classical civilization to ...
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  2. Rajakishore Nath (2009). Philosophy of Artificial Intelligence: A Critique of the Mechanistic Theory of Mind. Universal Publishers.score: 161.0
    This book deals with the major philosophical issues in the theoretical framework of Artificial Intelligence (AI) in particular and cognitive science in general.
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  3. Margaret A. Boden (ed.) (1990). The Philosophy of Artificial Intelligence. Oxford University Press.score: 161.0
    This interdisciplinary collection of classical and contemporary readings provides a clear and comprehensive guide to the many hotly-debated philosophical issues at the heart of artificial intelligence.
     
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  4. A. Fuhrmann & Hans Rott (eds.) (1996). Logic, Action, and Information: Essays on Logic in Philosophy and Artificial Intelligence. W. De Gruyter.score: 145.0
    Janusz Czelakowski Elements of Formal Action Theory 1. Elementary Action Systems 1.1 Introductory Remarks. In contemporary literature one may distinguish ...
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  5. D. Bruce Anderson (ed.) (1974). After Leibniz ...: Discussions on Philosophy and Artificial Intelligence. Available From the National Technical Information Service.score: 145.0
     
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  6. Todd C. Moody (1993). Philosophy and Artificial Intelligence. Prentice-Hall.score: 145.0
  7. Viola Schiaffonati (2003). A Framework for the Foundation of the Philosophy of Artificial Intelligence. Minds and Machines 13 (4):537-552.score: 144.0
    The peculiarity of the relationship between philosophy and Artificial Intelligence (AI) has been evidenced since the advent of AI. This paper aims to put the basis of an extended and well founded philosophy of AI: it delineates a multi-layered general framework to which different contributions in the field may be traced back. The core point is to underline how in the same scenario both the role of philosophy on AI and role of AI on (...) must be considered. Moreover, this framework is revised and extended in the light of the consideration of a type of multiagent system devoted to afford the issue of scientific discovery both from a conceptual and from a practical point of view. (shrink)
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  8. Raimo Tuomela (1996). Philosophy and Distributed Artificial Intelligence: The Case of Joint Intention. In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley.score: 130.0
    In current philosophical research the term 'philosophy of social action' can be used - and has been used - in a broad sense to encompass the following central research topics: 1) action occurring in a social context; this includes multi-agent action; 2) joint attitudes (or "we-attitudes" such as joint intention, mutual belief) and other social attitudes needed for the explication and explanation of social action; 3) social macro-notions, such as actions performed by social groups and properties of social groups (...)
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  9. Hutan Ashrafian (forthcoming). AIonAI: A Humanitarian Law of Artificial Intelligence and Robotics. Science and Engineering Ethics:1-12.score: 129.0
    The enduring progression of artificial intelligence and cybernetics offers an ever-closer possibility of rational and sentient robots. The ethics and morals deriving from this technological prospect have been considered in the philosophy of artificial intelligence, the design of automatons with roboethics and the contemplation of machine ethics through the concept of artificial moral agents. Across these categories, the robotics laws first proposed by Isaac Asimov in the twentieth century remain well-recognised and esteemed due to (...)
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  10. John L. Pollock (2000). Rationality in Philosophy and Artificial Intelligence. In The Proceedings of the Twentieth World Congress of Philosophy, Volume 9: Philosophy of Mind. Charlottesville: Philosophy Doc Ctr. 123-132.score: 121.0
    I argue here that sophisticated AI systems, with the exception of those aimed at the psychological modeling of human cognition, must be based on general philosophical theories of rationality and, conversely, philosophical theories of rationality should be tested by implementing them in AI systems. So the philosophy and the AI go hand in hand. I compare human and generic rationality within a broad philosophy of AI and conclude by suggesting that ultimately, virtually all familiar philosophical problems will turn (...)
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  11. William J. Rapaport (1986). Philosophy of Artificial Intelligence: A Course Outline. Teaching Philosophy 9 (2):103-120.score: 119.0
    In the Fall of 1983, I offered a junior/senior-level course in Philosophy of Artificial Intelligence, in the Department of Philosophy at SUNY Fredonia, after returning there from a year’s leave to study and do research in computer science and artificial intelligence (AI) at SUNY Buffalo. Of the 30 students enrolled, most were computerscience majors, about a third had no computer background, and only a handful had studied any philosophy. (I might note that enrollments (...)
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  12. Paul Thagard (1982). Artificial Intelligence, Psychology, and the Philosophy of Discovery. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1982:166 - 175.score: 119.0
    Buchanan and Darden have provided compelling reasons why philosophers of science concerned with the nature of scientific discovery should be aware of current work in artificial intelligence. This paper contends that artificial intelligence is even more than a source of useful analogies for the philosophy of discovery: the two fields are linked by interfield connections between philosophy of science and cognitive psychology and between cognitive psychology and artificial intelligence. Because the philosophy (...)
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  13. Jarek Gryz (2013). The Frame Problem in Artificial Intelligence and Philosophy. Filozofia Nauki 2 (2):15-30.score: 116.0
    The field of Artificial Intelligence has been around for over 60 years now. Soon after its inception, the founding fathers predicted that within a few years an intelligent machine would be built. That prediction failed miserably. Not only hasn’t an intelligent machine been built, but we are not much closer to building one than we were some 50 years ago. Many reasons have been given for this failure, but one theme has been dominant since its advent in 1969: (...)
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  14. Olivier Houdé (ed.) (2004). Dictionary of Cognitive Science: Neuroscience, Psychology, Artificial Intelligence, Linguistics, and Philosophy. Psychology Press.score: 116.0
    A translation of the renowned French reference book, Vocabulaire de sciences cognitives , the Dictionary of Cognitive Science presents comprehensive definitions of more than 120 terms. The editor and advisory board of specialists have brought together 60 internationally recognized scholars to give the reader a comprehensive understanding of the most current and dynamic thinking in cognitive science. Topics range from Abduction to Writing, and each entry covers its subject from as many perspectives as possible within the domains of psychology, (...) intelligence, neuroscience, philosophy, and linguistics. This multidisciplinary work is an invaluable resource for all collections. (shrink)
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  15. Varol Akman (1998). Book Review -- John Haugeland (Editor), Mind Design II: Philosophy, Psychology, and Artificial Intelligence. [REVIEW] .score: 116.0
    This is a review of Mind Design II: Philosophy, Psychology, and Artificial Intelligence, edited by John Haugeland, published by MIT Press in 1997.
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  16. John Haugeland (ed.) (1997). Mind Design II: Philosophy, Psychology, Artificial Intelligence. Cambridge: MIT Press.score: 115.0
    Contributors: Rodney A. Brooks, Paul M. Churchland, Andy Clark, Daniel C. Dennett, Hubert L. Dreyfus, Jerry A. Fodor, Joseph Garon, John Haugeland, Marvin...
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  17. John L. Pollock (1990). Philosophy and Artificial Intelligence. Philosophical Perspectives 4:461-498.score: 115.0
  18. Pompeu Casanovas Romeu (ed.) (2007). Trends in Legal Knowledge: The Semantic Web and the Regulation of Electronic Social Systems: Papers From the B-4 Workshop on Artificial Intelligence and Law, May 25th- 27th 2005: Xxii World Congress of Philosophy Ivr '05 Granada, May 24th-29th 2005. [REVIEW] European Press Academic Pub..score: 115.0
  19. Douglas N. Walton (2008). Witness Testimony Evidence: Argumentation, Artificial Intelligence, and Law. Cambridge University Press.score: 114.0
    Recent work in artificial intelligence has increasingly turned to argumentation as a rich, interdisciplinary area of research that can provide new methods related to evidence and reasoning in the area of law. Douglas Walton provides an introduction to basic concepts, tools and methods in argumentation theory and artificial intelligence as applied to the analysis and evaluation of witness testimony. He shows how witness testimony is by its nature inherently fallible and sometimes subject to disastrous failures. At (...)
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  20. Lawrence B. Solum (1992). Legal Personhood for Artificial Intelligences. North Carolina Law Review 70:1231.score: 107.0
    Could an artificial intelligence become a legal person? As of today, this question is only theoretical. No existing computer program currently possesses the sort of capacities that would justify serious judicial inquiry into the question of legal personhood. The question is nonetheless of some interest. Cognitive science begins with the assumption that the nature of human intelligence is computational, and therefore, that the human mind can, in principle, be modelled as a program that runs on a computer. (...)
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  21. Martin Ringle (1979). Philosophy and Artificial Intelligence. In , Philosophical Perspectives in Artificial Intelligence. Humanities Press.score: 101.0
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  22. Maria Nowakowska (1986). Cognitive Sciences: Basic Problems, New Perspectives and Implications for Artificial Intelligence. Academic Press.score: 100.0
  23. Erwin Lucius & Şafak Ural (eds.) (1999). Artificial Intelligence, Language and Thought: Third Meeting of [Sic] Istanbul-Vienna Philosophical Circle. Isis Press.score: 100.0
  24. J. E. Tiles, G. T. McKee & G. C. Dean (eds.) (1990). Evolving Knowledge in Natural Science and Artificial Intelligence. Pitman.score: 100.0
  25. Peter Wahlgren (1992). Automation of Legal Reasoning: A Study on Artificial Intelligence and Law. Kluwer Law and Taxation Publishers.score: 100.0
  26. Craig DeLancey (2001). Passionate Engines: What Emotions Reveal About the Mind and Artificial Intelligence. Oxford University Press.score: 99.0
    The emotions have been one of the most fertile areas of study in psychology, neuroscience, and other cognitive disciplines. Yet as influential as the work in those fields is, it has not yet made its way to the desks of philosophers who study the nature of mind. Passionate Engines unites the two for the first time, providing both a survey of what emotions can tell us about the mind, and an argument for how work in the cognitive disciplines can help (...)
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  27. Evan Selinger (2008). Collins's Incorrect Depiction of Dreyfus's Critique of Artificial Intelligence. Phenomenology and the Cognitive Sciences 7 (2):301-308.score: 99.0
    Harry Collins interprets Hubert Dreyfus’s philosophy of embodiment as a criticism of all possible forms of artificial intelligence. I argue that this characterization is inaccurate and predicated upon a misunderstanding of the relevance of phenomenology for empirical scientific research.
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  28. John McCarthy, Artificial Intelligence and Philosophy.score: 99.0
    AI needs many ideas that have hitherto been studied only by philosophers. This is because a robot, if it is to have human level intelligence and ability to learn from its experience, needs a general world view in which to organize facts. It turns out that many philosophical problems take new forms when thought about in terms of how to design a robot. Some approaches to philosophy are helpful and others are not.
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  29. Hans F. M. Crombag (1993). On the Artificiality of Artificial Intelligence. Artificial Intelligence and Law 2 (1):39-49.score: 98.0
    In this article the question is raised whether artificial intelligence has any psychological relevance, i.e. contributes to our knowledge of how the mind/brain works. It is argued that the psychological relevance of artificial intelligence of the symbolic kind is questionable as yet, since there is no indication that the brain structurally resembles or operates like a digital computer. However, artificial intelligence of the connectionist kind may have psychological relevance, not because the brain is a (...)
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  30. Jean-Gabriel Ganascia (2010). Epistemology of AI Revisited in the Light of the Philosophy of Information. Knowledge, Technology and Policy 23 (1-2):57-73.score: 96.0
    Artificial intelligence has often been seen as an attempt to reduce the natural mind to informational processes and, consequently, to naturalize philosophy. The many criticisms that were addressed to the so-called “old-fashioned AI” do not concern this attempt itself, but the methods it used, especially the reduction of the mind to a symbolic level of abstraction, which has often appeared to be inadequate to capture the richness of our mental activity. As a consequence, there were many efforts (...)
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  31. Debasis Patnaik (forthcoming). Theorizing Change in Artificial Intelligence: Inductivising Philosophy From Economic Cognition Processes. [REVIEW] AI and Society:1-9.score: 93.7
    Economic value additions to knowledge and demand provide practical, embedded and extensible meaning to philosophizing cognitive systems. Evaluation of a cognitive system is an empirical matter. Thinking of science in terms of distributed cognition (interactionism) enlarges the domain of cognition. Anything that actually contributes to the specific quality of output of a cognitive system is part of the system in time and/or space. Cognitive science studies behaviour and knowledge structures of experts and categorized structures based on underlying structures. Knowledge representation (...)
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  32. Mike Oaksford (1990). Clark Glymour, Richard Scheines, Peter Spirtes and Kevin Kelly, Discovering Causal Structure: Artificial Intelligence, Philosophy of Science and Statistical Modelling Reviewed By. Philosophy in Review 10 (1):19-21.score: 93.0
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  33. Rolf Struve (1992). Wissensbasierte Systeme — Utopie Und Realität. Journal for General Philosophy of Science 23 (2):315 - 322.score: 92.0
    Knowledge-based systems - Utopia and Reality. The following article is a response to K. Mainzer's 'Knowledge-Based Systems; Remarks on the Philosophy of Technology and Artificial Intelligence'. We show, that Mainzer does not reach any of his aims - to analyse the possibilities and limits of AI-technology, - to reduce anxiousness and hostility against AI, which is motivated by phantastic speculations, - to evaluate the factual impact of AI on our lives and on society. His article contributes on (...)
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  34. Rolf Struve (1992). Wissensbasierte Systeme — Utopie Und RealitätKnowledge-Based Systems — Utopia and Reality. Journal for General Philosophy of Science 23 (2):315-322.score: 92.0
    The following article is a response to K. Mainzer's ‘Knowledge-Based Systems; Remarks on the Philosophy of Technology and Artificial Intelligence’. We show, that Mainzer does not reach any of his aimsto analyse the possibilities and limits of AI-technology.to reduce anxiousness and hostility against AI, which is motivated by phantastic speculations.to evaluate the factual impact of AI on our lives and on society.His article contributes on the contrary to phantastic speculations, which are not technologically justified in any way. (...)
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  35. Brian L. Keeley (1994). Against the Global Replacement: On the Application of the Philosophy of Artificial Intelligence to Artificial Life. In C. G. Langton (ed.), Artificial Life Iii: Proceedings of the Workshop on Artificial Life. Reading, Mass: Addison-Wesley.score: 90.0
  36. Lindley Darden (1982). Artificial Intelligence and Philosophy of Science: Reasoning by Analogy in Theory Construction. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1982:147 - 165.score: 90.0
    This paper examines the hypothesis that analogies may play a role in the generation of new ideas that are built into new explanatory theories. Methods of theory construction by analogy, by failed analogy, and by modular components from several analogies are discussed. Two different analyses of analogy are contrasted: direct mapping (Mary Hesse) and shared abstraction (Michael Genesereth). The structure of Charles Darwin's theory of natural selection shows various analogical relations. Finally, an "abstraction for selection theories" is shown to be (...)
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  37. Klaus Mainzer (1990). Knowledge-Based Systems. Journal for General Philosophy of Science 21 (1):47-74.score: 90.0
    No kind of technology has had such a profound effect upon our lives and society as the new knowledge-based systems which start to overcome the traditional computer technology. Few areas of science raise such high expectations and meet with so much sceptical resistance as Artificial Intelligence (AI). So it is the task of philosophy of science and technology to analyze the factual methodological possibilities of AI-technology. After a historical sketch of AI-development (Chapter 2), the technological foundations of (...)
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  38. J. Preston (1997). Review. Artificial Intelligence and Scientific Method. Donald Gillies. Philosophy and AI: Essays at the Interface. Robert Cummins, John Pollock (Eds). [REVIEW] British Journal for the Philosophy of Science 48 (4):610-612.score: 90.0
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  39. Keith Gunderson (1968). Minnesota Center for the Philosophy of Science Although the Last International Conference on Cybernetics Was Held in 1955, the Ensuing Blitzkrieg of Articles and Books in the Overlapping Areas of Artificial Intelligence (AI) and Computer Simu. In Raymond Klibansky (ed.), Contemporary Philosophy. Firenze, la Nuova Italia. 2--416.score: 90.0
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  40. J. Margolis (1986). Information, Artificial, Intelligence, and the Praxical in Philosophy and Technology II. Information Technology and Computers in Theory and Practice. Boston Studies in the Philosophy of Science 90:171-186.score: 90.0
     
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  41. Don Ross (1991). Margaret A Boden, Ed., The Philosophy of Artificial Intelligence Reviewed By. Philosophy in Review 11 (4):225-230.score: 90.0
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  42. B. Marchal (1990). Theoretical Foundations for Artificial-Intelligence and Philosophy of the Mind. Revue Internationale de Philosophie 44 (172):104-107.score: 88.0
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  43. Vincent C. Müller (2012). Introduction: Philosophy and Theory of Artificial Intelligence. [REVIEW] Minds and Machines 22 (2):67-69.score: 87.0
  44. Tracy B. Henley (1990). Natural Problems and Artificial Intelligence. Behavior and Philosophy 18 (2):43-55.score: 87.0
    Artificial Intelligence has become big business in the military and in many industries. In spite of this growth there still remains no consensus about what AI really is. The major factor which seems to be responsible for this is the lack of agreement about the relationship between behavior and intelligence. In part certain ethical concerns generated from saying who, what and how intelligence is determined may be facilitating this lack of agreement.
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  45. Sebastian Lutz (2012). Artificial Language Philosophy of Science. European Journal for Philosophy of Science (Browse Results) 2 (2):181–203.score: 87.0
    Abstract Artificial language philosophy (also called ‘ideal language philosophy’) is the position that philosophical problems are best solved or dissolved through a reform of language. Its underlying methodology—the development of languages for specific purposes—leads to a conventionalist view of language in general and of concepts in particular. I argue that many philosophical practices can be reinterpreted as applications of artificial language philosophy. In addition, many factually occurring interrelations between the sciences and philosophy of science (...)
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  46. Guy Lancaster (2009). Minds and Computers: An Introduction to the Philosophy of Artificial Intelligence. By Matt Carter. Heythrop Journal 50 (3):565-565.score: 87.0
  47. Avinash De Sousa (2013). Towards an Integrative Theory of Consciousness: Part 2 (An Anthology of Various Other Models). Mens Sana Monographs 11 (1):151.score: 87.0
    The study of consciousness has today moved beyond neurobiology and cognitive models. In the past few years, there has been a surge of research into various newer areas. The present article looks at the non-neurobiological and non-cognitive theories regarding this complex phenomenon, especially ones that self-psychology, self-theory, artificial intelligence, quantum physics, visual cognitive science and philosophy have to offer. Self-psychology has proposed the need to understand the self and its development, and the ramifications of the self for (...)
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  48. Alan Ross Anderson & Kenneth M. Sayre (1966). Recognition: A Study in the Philosophy of Artificial Intelligence. Philosophical Quarterly 16 (65):387.score: 87.0
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  49. John Bryant (1991). Systems Theory and Scientific Philosophy: An Application of the Cybernetics of W. Ross Ashby to Personal and Social Philosophy, the Philosophy of Mind, and the Problems of Artificial Intelligence. University Press of America.score: 87.0
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  50. Jack Copeland (ed.) (2004). The Essential Turing: Seminal Writings in Computing, Logic, Philosophy, Artificial Intelligence, and Artificial Life: Plus the Secrets of Enigma. Oup.score: 87.0
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