Results for 'Distributed intelligence'

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  1. Connectionist representations for natural language: Old and new Noel E. sharkey department of computer science university of exeter.Localist V. Distributed - 1990 - In G. Dorffner (ed.), Konnektionismus in Artificial Intelligence Und Kognitionsforschung. Berlin: Springer-Verlag. pp. 252--1.
  2. Keith S. Decker.Intelligence Testbeds - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 9--119.
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  3. Jacques Ferber.Reactive Distributed Artificial - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 287.
     
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  4. Michael Wooldridge.Modeling Distributed Artificial - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 269.
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  5.  41
    Distributive justice and cognitive enhancement in lower, normal intelligence.Mikael Dunlop & Julian Savulescu - 2014 - Monash Bioethics Review 32 (3-4):189-204.
    There exists a significant disparity within society between individuals in terms of intelligence. While intelligence varies naturally throughout society, the extent to which this impacts on the life opportunities it affords to each individual is greatly undervalued. Intelligence appears to have a prominent effect over a broad range of social and economic life outcomes. Many key determinants of well-being correlate highly with the results of IQ tests, and other measures of intelligence, and an IQ of 75 (...)
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  6.  48
    Distributed artificial intelligence and social science: Critical issues.Cristiano Castelfranchi & Rosaria Conte - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley.
  7.  5
    Intelligent Coordination Distribution of the Whole Supply Chain Based on the Internet of Things.Hongxiu Cui - 2021 - Complexity 2021:1-12.
    In this paper, through the intelligent research of the whole process of logistics and distribution with the Internet of Things supply chain, we study how to improve the development of the cold chain, reduce the loss in circulation, improve the social and economic benefits, and carry out intelligent information collection, monitoring, management, and information tracing of the whole cold chain. This paper analyzes and empirically studies the impact of key technologies of the Internet of Things in cold chain coordination from (...)
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  8.  76
    Distributed artificial intelligence from a socio-cognitive standpoint: Looking at reasons for interaction. [REVIEW]Maria Miceli, Amedo Cesta & Paola Rizzo - 1995 - AI and Society 9 (4):287-320.
    Distributed Artificial Intelligence (DAI) deals with computational systems where several intelligent components interact in a common environment. This paper is aimed at pointing out and fostering the exchange between DAI and cognitive and social science in order to deal with the issues of interaction, and in particular with the reasons and possible strategies for social behaviour in multi-agent interaction is also described which is motivated by requirements of cognitive plausibility and grounded the notions of power, dependence and help. (...)
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  9. A distributed artificial intelligence reading of Todorov's The Conquest of America.J. E. Doran - 1990 - In Tadeusz Buksiński (ed.), Interpretation in the Humanities. Uniwersytet Im. Adama Mickiewicza W Poznaniu.
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    Organizational intelligence and distributed artificial intelligence.Stefan Kirn - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley.
  11.  3
    Intelligent distributed and networking systems.Jacek Maitan - 1991 - In P. A. Flach (ed.), Future Directions in Artificial Intelligence. New York: Elsevier Science.
  12.  43
    Distributed Systems, Parallel Processing, and the Intelligent Computer.D. Frank Hsu - 1986 - Thought: Fordham University Quarterly 61 (4):401-411.
  13.  8
    Reactive distributed artificial intelligence: Principles and applications.Jacques Ferber - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 287--314.
  14.  11
    IDOCS: Intelligent distributed ontology consensus system - The use of machine learning in retinal drusen phenotyping.George Thomas, Michael A. Grassi, John R. Lee, Albert O. Edwards, Michael B. Gorin, Ronald Klein, Thomas L. Casavant, Todd E. Scheetz, Edwin M. Stone & Andrew B. Williams - unknown
    PurposeTo use the power of knowledge acquisition and machine learning in the development of a collaborative computer classification system based on the features of age-related macular degeneration (AMD).MethodsA vocabulary was acquired from four AMD experts who examined 100 ophthalmoscopic images. The vocabulary was analyzed, hierarchically structured, and incorporated into a collaborative computer classification system called IDOCS. Using this system, three of the experts examined images from a second set of digital images compiled from more than 1000 patients with AMD. Images (...)
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  15.  9
    Distributed artificial intelligence.Zhongzhi Shi - 1991 - In P. A. Flach (ed.), Future Directions in Artificial Intelligence. New York: Elsevier Science.
  16.  53
    ARCHON: A distributed artificial intelligence system for industrial applications.David Cockburn & Nick R. Jennings - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 319--344.
  17.  28
    A generic distributed simulation system for intelligent agent design and evaluation.John Anderson - forthcoming - Proceedings of the Tenth Conference on Ai, Simulation and Planning, Ais-2000, Society for Computer Simulation International.
  18.  87
    Philosophy and distributed artificial intelligence: The case of joint intention.Raimo Tuomela - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley.
    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 such (...)
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  19.  10
    Applications of distributed artificial intelligence in industry.H. Van Dyke Parunak - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 139-164.
  20.  9
    Logical foundations of distributed artificial intelligence.Eric Werner - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 57--117.
  21.  12
    User design issues for distributed artificial intelligence.Lynne E. Hall - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley.
  22.  15
    An overview of distributed artificial intelligence.Bernard Moulin & Brahim Chaib-Draa - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 1--3.
  23.  56
    Coordination techniques for distributed artificial intelligence.Nick R. Jennings - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 187--210.
  24.  5
    Planning in distributed artificial intelligence.Edmund Durfee - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 245.
  25.  12
    Hybrid artificial intelligence approaches on vehicle routing problem in logistics distribution.Dragan Simić & Svetlana Simić - 2012 - In Emilio Corchado, Vaclav Snasel, Ajith Abraham, Michał Woźniak, Manuel Grana & Sung-Bae Cho (eds.), Hybrid Artificial Intelligent Systems. Springer. pp. 208--220.
  26. Artificial Intelligence: A Philosophical Introduction.Jack Copeland - 1993 - Wiley-Blackwell.
    Presupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding. There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence and neuroscience. (...)
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  27.  67
    Ambient Intelligence, Criminal Liability and Democracy.Mireille Hildebrandt - 2008 - Criminal Law and Philosophy 2 (2):163-180.
    In this contribution we will explore some of the implications of the vision of Ambient Intelligence (AmI) for law and legal philosophy. AmI creates an environment that monitors and anticipates human behaviour with the aim of customised adaptation of the environment to a person’s inferred preferences. Such an environment depends on distributed human and non-human intelligence that raises a host of unsettling questions around causality, subjectivity, agency and (criminal) liability. After discussing the vision of AmI we will (...)
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  28. Artificial Intelligence: A Philosophical Introduction.B. Jack Copeland - 1993 - Cambridge: Blackwell.
    Presupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding.There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence and neuroscience. John (...)
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  29.  8
    Image Recognition and Simulation Based on Distributed Artificial Intelligence.Tao Fan - 2021 - Complexity 2021:1-11.
    This paper studies the traditional target classification and recognition algorithm based on Histogram of Oriented Gradients feature extraction and Support Vector Machine classification and applies this algorithm to distributed artificial intelligence image recognition. Due to the huge number of images, the general detection speed cannot meet the requirements. We have improved the HOG feature extraction algorithm. Using principal component analysis to perform dimensionality reduction operations on HOG features and doing distributed artificial intelligence image recognition experiments, the (...)
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  30.  14
    Open Information Systems Semantics for distributed artificial intelligence.Carl Hewitt - 1991 - Artificial Intelligence 47 (1-3):79-106.
  31.  21
    Temporal belief logics for modelling distributed artificial intelligence systems.Michael Wooldridge - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 269--286.
  32.  10
    IMAGINE: An integrated environment for constructing distributed artificial intelligence systems.Donald D. Steiner - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 345--364.
  33.  4
    Learning from others: Exchange of classification rules in intelligent distributed systems.Dominik Fisch, Martin Jänicke, Edgar Kalkowski & Bernhard Sick - 2012 - Artificial Intelligence 187-188 (C):90-114.
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  34.  12
    Emotional intelligence and the second language acquisition in virtual learning environment.N. V. Bhatti - forthcoming - Philosophical Problems of IT and Cyberspace (PhilIT&C).
    Gardner’s theory of multiple intelligences has been further developed to focus on the research of human cognitive activities. Thus, the concept of emotional intelligence, which is the topic of the current paper, was introduced by John D. Mayer, Peter Salovey and ‎Daniel Goleman. General intelligence can be defined as the capacity to carry out abstract reasoning to understand meanings, to recognize the similarities and differences between two concepts and to make generalizations. Emotional intelligence is not a part (...)
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  35. Distributed Identity.Phillip Barron - 2022 - Dissertation, University of Connecticut
    This dissertation offers and defends a phenomenological account of personal identity. It does so critically in conversation with Anglo-analytical traditions and varieties of other philosophical traditions from around the world, especially Zen Buddhism. Chapter One brings together three areas of philosophy: the multiple realizability thesis from philosophy of science, the logical pluralist position from philosophical logic, and the various conceptions of personhood from metaphysics. I argue that even though the divide in the literature on the metaphysics of personal identity is (...)
     
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  36. Future progress in artificial intelligence: A survey of expert opinion.Vincent C. Müller & Nick Bostrom - 2016 - In Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence. Cham: Springer. pp. 553-571.
    There is, in some quarters, concern about high–level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development, and how fast they see these developing. (...)
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  37.  80
    Generalized distributivity operators.Peter Lasersohn - 1998 - Linguistics and Philosophy 21 (1):83-93.
    Presents a series of generalizations of distributivity operators across a type hierarchy, in order to account for collective-distributive ambiguities for non-subject arguments.
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  38. An Intelligent Tutoring System for Learning Computer Network CCNA.Izzeddin A. Alshawwa, Mohammed Al-Shawwa & Samy S. Abu-Naser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (2):28-36.
    Abstract: Networking is one of the most important areas currently used for data transfer and enterprise management. It also includes the security aspect that enables us to protect our network to prevent hackers from accessing the organization's data. In this paper, we would like to learn what the network is and how it works. And what are the basics of the network since its emergence and know the mechanism of action components. After reading this paper - even if you do (...)
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  39. Recursive distributed representations.Jordan B. Pollack - 1990 - Artificial Intelligence 46 (1-2):77-105.
  40.  92
    Distributivity strengthens reciprocity, collectivity weakens it.Hana Filip & Gregory N. Carlson - 2001 - Linguistics and Philosophy 24 (4):417-466.
    In this paper we examine interactions of the reciprocal with distributive and collective operators, which are encoded by prefixes on verbs expressing the reciprocal relation: namely, the Czech distributive po and the collectivizing na-. The theoretical import of this study is two-fold. First, it contributes to our knowledge of how word-internal operators interact with phrasal syntax/semantics. Second, the prefixes po and na generate (a range of) readings of reciprocal sentences for which the Strongest Meaning Hypothesis (SMH) proposed by Dalrymple et (...)
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  41. Rethinking distributed representation.William Ramsey - 1995 - Acta Analytica 10 (14):9-25.
  42. Rawls, responsibility, and distributive justice.Richard Arneson - manuscript
    The theory of justice pioneered by John Rawls explores a simple idea--that the concern of distributive justice is to compensate individuals for misfortune. Some people are blessed with good luck, some are cursed with bad luck, and it is the responsibility of society--all of us regarded collectively--to alter the distribution of goods and evils that arises from the jumble of lotteries that constitutes human life as we know it. Some are lucky to be born wealthy, or into a favorable socializing (...)
     
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  43. The distribution of numbers and the comprehensiveness of reasons.Veronique Munoz-Darde - 2005 - Proceedings of the Aristotelian Society 105 (2):207–233.
    In this paper, I concentrate on two themes: to what extent numbers bear on an agent's duties, and how numbers should relate to social policy. In the first half of the paper I consider the abstract case of a choice between saving two people and saving one, and my focus is on the contrast between a duty to act and a reason which merely makes an action intelligible. In the second half, I turn to the issue of social policy and (...)
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  44. The logic of distributive bilattices.Félix Bou & Umberto Rivieccio - 2011 - Logic Journal of the IGPL 19 (1):183-216.
    Bilattices, introduced by Ginsberg as a uniform framework for inference in artificial intelligence, are algebraic structures that proved useful in many fields. In recent years, Arieli and Avron developed a logical system based on a class of bilattice-based matrices, called logical bilattices, and provided a Gentzen-style calculus for it. This logic is essentially an expansion of the well-known Belnap–Dunn four-valued logic to the standard language of bilattices. Our aim is to study Arieli and Avron’s logic from the perspective of (...)
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  45.  24
    The Age of Artificial Intelligences: A Personal Reflection.Rafael` Capurro - 2020 - International Review of Information Ethics 28.
    The following paper presents both a historical and personal account of the societal and ethical issues arising in the development of artificial intelligence, tracking, where I was involved, the issues from the nineteen seventies onward. My own involvement in the AI narrative begins with the early discussions around whether machines can think. These first discussions, in time, evolved secondly, with the rise of the internet in the nineties, into perceptions of AI as distributed intelligence, addressing its impact (...)
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  46.  7
    Emotional intelligence and the second language acquisition in virtual learning environment.Н. В Бхатти - 2023 - Philosophical Problems of IT and Cyberspace (PhilIT&C) 2:4-17.
    Gardner’s theory of multiple intelligences has been further developed to focus on the research of human cognitive activities. Thus, the concept of emotional intelligence, which is the topic of the current paper, was introduced by John D. Mayer, Peter Salovey and ‎Daniel Goleman. General intelligence can be defined as the capacity to carry out abstract reasoning to understand meanings, to recognize the similarities and differences between two concepts and to make generalizations. Emotional intelligence is not a part (...)
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  47.  7
    Life, Intelligence, and the Selection of Universes.Rüdiger Vaas - 2019 - In Yordanov Georgi Georgiev, John M. Smart & Claudio L. Flores Martinez (eds.), Evolution, Development and Complexity. Springer. pp. 93-133.
    Complexity and life as we know it depend crucially on the laws and constants of nature as well as the boundary conditions, which seem at least partly “fine-tuned.” That deserves an explanation: Why are they the way they are? This essay discusses and systematizes the main options for answering these foundational questions. Fine-tuning might just be an illusion, or a result of irreducible chance, or nonexistent because nature could not have been otherwise (which might be shown within a fundamental theory (...)
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  48.  9
    Distributed revision of composite beliefs.Judea Pearl - 1987 - Artificial Intelligence 33 (2):173-215.
  49.  20
    Raymond Turner. Logics for artificial intelligence. Ellis Horwood series in artificial intelligence. Ellis Horwood, Chichester 1984, also distributed by Halsted Press, New York, 121 pp. [REVIEW]Francis Jeffry Pelletier & Lenhart K. Schubert - 1991 - Journal of Symbolic Logic 56 (1):339-340.
  50. Coercive paternalism and the intelligence continuum.Nathan Cofnas - 2020 - Behavioural Public Policy 4 (1):88-107.
    Thaler and Sunstein advocate 'libertarian paternalism'. A libertarian paternalist changes the conditions under which people act so that their cognitive biases lead them to choose what is best for themselves. Although libertarian paternalism manipulates people, Thaler and Sunstein say that it respects their autonomy by preserving the possibility of choice. Conly argues that libertarian paternalism does not go far enough, since there is no compelling reason why we should allow people the opportunity to choose to bring disaster upon themselves if (...)
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