30 found
  1.  6
    Global Workspace Dynamics: Cortical “Binding and Propagation” Enables Conscious Contents.Bernard J. Baars, Stan Franklin & Thomas Zoega Ramsoy - 2013 - Frontiers in Psychology 4.
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  2. How Conscious Experience and Working Memory Interact.Bernard J. Baars & Stan Franklin - 2003 - Trends in Cognitive Sciences 7 (4):166-172.
  3. Consciousness is Computational: The Lida Model of Global Workspace Theory.Bernard J. Baars & Stan Franklin - 2009 - International Journal of Machine Consciousness 1 (1):23-32.
  4. Ida: A Conscious Artifact?Stan Franklin - 2003 - Journal of Consciousness Studies 10 (4):47-66.
  5.  45
    Consciousness and Ethics: Artificially Conscious Moral Agents.Wendell Wallach, Colin Allen & Stan Franklin - 2011 - International Journal of Machine Consciousness 3 (01):177-192.
  6. A Conceptual and Computational Model of Moral Decision Making in Human and Artificial Agents.Wendell Wallach, Stan Franklin & Colin Allen - 2010 - Topics in Cognitive Science 2 (3):454-485.
    Recently, there has been a resurgence of interest in general, comprehensive models of human cognition. Such models aim to explain higher-order cognitive faculties, such as deliberation and planning. Given a computational representation, the validity of these models can be tested in computer simulations such as software agents or embodied robots. The push to implement computational models of this kind has created the field of artificial general intelligence (AGI). Moral decision making is arguably one of the most challenging tasks for computational (...)
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  7.  8
    Resilient Architectures to Facilitate Both Functional Consciousness and Phenomenal Consciousness in Machines.Uma Ramamurthy & Stan Franklin - 2009 - International Journal of Machine Consciousness 1 (2):243-253.
  8.  42
    Evolutionary Pressures for Perceptual Stability and Self as Guides to Machine Consciousness.Stan Franklin, Sidney D'Mello, Bernard J. Baars & Uma Ramamurthy - 2009 - International Journal of Machine Consciousness 1 (1):99-110.
  9.  30
    Global Workspace Theory, Shanahan, and Lida.Stan Franklin - 2011 - International Journal of Machine Consciousness 3 (02):327-337.
  10.  43
    A Software Agent Model of Consciousness.Stan Franklin & Art Graesser - 1999 - Consciousness and Cognition 8 (3):285-301.
    Baars (1988, 1997) has proposed a psychological theory of consciousness, called global workspace theory. The present study describes a software agent implementation of that theory, called ''Conscious'' Mattie (CMattie). CMattie operates in a clerical domain from within a UNIX operating system, sending messages and interpreting messages in natural language that organize seminars at a university. CMattie fleshes out global workspace theory with a detailed computational model that integrates contemporary architectures in cognitive science and artificial intelligence. Baars (1997) lists the psychological (...)
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  11. How Deliberate, Spontaneous, and Unwanted Memories Emerge in a Computational Model of Consciousness.Bernard J. Baars, Uma Ramamurthy & Stan Franklin - 2007 - In John H. Mace (ed.), Involuntary Memory. New Perspectives in Cognitive Psychology. Blackwell. pp. 177-207.
  12.  80
    Consciousness and Conceptual Learning in a Socially Situated Agent.Myles Bogner, Uma Ramamurthy & Stan Franklin - 2000 - In Kerstin Dauthenhahn (ed.), Human Cognition and Social Agent Technology. Amsterdam: John Benjamins. pp. 113--135.
  13. Computational Models of Consciousness: A Taxonomy and Some Examples.Ron Sun & Stan Franklin - 2007 - In Philip David Zelazo, Morris Moscovitch & Evan Thompson (eds.), Cambridge Handbook of Consciousness. Cambridge: Cambridge University Press. pp. 151--174.
  14.  34
    Conscious Software: A Computational View of Mind.Stan Franklin - manuscript
  15.  50
    Walter J. Freeman, How Brains Make Up Their Minds.Stan Franklin - 2007 - Minds and Machines 17 (3):353-356.
  16. An Action Selection Mechanism for "Conscious" Software Agents.Aregahegn S. Negatu & Stan Franklin - 2002 - Cognitive Science Quarterly. Special Issue 2 (3):362-384.
  17.  29
    Bridging the Gap: Dynamics as a Unified View of Cognition.Derek Harter, Arthur C. Graesser & Stan Franklin - 2001 - Behavioral and Brain Sciences 24 (1):45-46.
    Top-down dynamical models of cognitive processes, such as the one presented by Thelen et al., are important pieces in understanding the development of cognitive abilities in humans and biological organisms. Unlike standard symbolic computational approaches to cognition, such dynamical models offer the hope that they can be connected with more bottom-up, neurologically inspired dynamical models to provide a complete view of cognition at all levels. We raise some questions about the details of their simulation and about potential limitations of top-down (...)
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  18.  15
    Self-System in a Model of Cognition.Uma Ramamurthy, Stan Franklin & Pulin Agrawal - 2012 - International Journal of Machine Consciousness 4 (2):325-333.
  19.  4
    Global Workspace Agents.Stan Franklin - 1997 - Journal of Consciousness Studies 4 (4):322-324.
    In the target article, Baars has offered both a theory of consciousness and a strategy for scientifically testing the theory. This commentary is intended as an addendum. I'd like to suggest implementing global workspace agents as both an additional strategy toward scientific testing, and as a means of fleshing out the theory.
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  20.  33
    Sense and Nonsense: Comments on Horgan's Precis of the Undiscovered Mind. [REVIEW]Stan Franklin - 2001 - Brain and Mind 2 (2):231-234.
  21.  23
    Robert G. Burton, Ed., Natural and Artificial Minds, SUNY Series, Scientific Studies in Natural and Artificial Intelligence, Albany: State University of New York Press, 1993, VII + 245 Pp., $21.95 (Paper), ISBN 0-7914-1508-. [REVIEW]Stan Franklin - 1999 - Minds and Machines 9 (1):143-156.
  22.  18
    On Stability and Solvability (or, When Does a Neural Network Solve a Problem?).Stan Franklin & Max Garzon - 1992 - Minds and Machines 2 (1):71-83.
    The importance of the Stability Problem in neurocomputing is discussed, as well as the need for the study of infinite networks. Stability must be the key ingredient in the solution of a problem by a neural network without external intervention. Infinite discrete networks seem to be the proper objects of study for a theory of neural computability which aims at characterizing problems solvable, in principle, by a neural network. Precise definitions of such problems and their solutions are given. Some consequences (...)
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  23.  9
    A Conscious Artifact?Stan Franklin - 2003 - Journal of Consciousness Studies 10 (4-5):4-5.
    After discussing various types of consciousness, several approaches to machine consciousness, software agent, and global workspace theory, we describe a software agent, IDA, that is 'conscious' in the sense of implementing that theory of consciousness. IDA perceives, remembers, deliberates, negotiates, and selects actions, sometimes 'consciously'. She uses a variety of mechanisms, each of which is briefly described. It's tempting to think of her as a conscious artifact. Is such a view in any way justified? The remainder of the paper considers (...)
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  24.  10
    Commentary on R. Cummins' “Radical Connectionism”.Stan Franklin & Max Garzon - 1988 - Southern Journal of Philosophy 26 (S1):63-65.
  25. Cognitive Agents Architecture and Theory (CAAT).Stan Franklin - manuscript
    Cognition, writ broadly to include motivation and emotion, is best conceived of as control structure for autonomous agents . Autonomous agents are situated in a environment. They both sense and act on that environment, over time, so as to effect subsequent sensing. Examples of such agents include humans, animals, some mobile robots, some artificial life creatures (who "live" in a simulated environment on a computer) and some software agents (who "live" in a file system, a database, or on a network). (...)
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  26.  10
    Action Selection and Language Generation in "Conscious" Software Agents.Stan Franklin - manuscript
  27.  4
    The LIDA Model as a Foundational Architecture for AGI.Usef Faghihi & Stan Franklin - 2012 - In Pei Wang & Ben Goertzel (eds.), Theoretical Foundations of Artificial General Intelligence. Springer. pp. 103--121.
  28.  6
    Action Patterns, Conceptualization, and Artificial Intelligence.Stan Franklin - 1997 - Behavioral and Brain Sciences 20 (1):23-24.
    This commentary connects some of Glenberg's ideas to similar ideas from artificial intelligence. Second, it briefly discusses hidden assumptions relating to meaning, representations, and projectable properties. Finally, questions about mechanisms, mental imagery, and conceptualization in animals are posed.
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  29.  5
    Models as Implementations of a Theory, Rather Than Simulations: Dancing to a Different Drummer.Stan Franklin - 2001 - Behavioral and Brain Sciences 24 (6):1059-1059.
    Robots, as well as software agents, can be of use in biology as implementations of a theory rather than as simulations of specific real world target systems. Such implementations generate hypotheses rather than representing them. Their behavior is not predicted, but rather observed, and is not expected to duplicate that of a target system. Scientific knowledge is gained through the testing of generated hypotheses.
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  30. Evolutionary Pressures and a Stable World for Animals and Robots: A Commentary on Merker ☆.Stan Franklin - 2005 - Consciousness and Cognition 10 (1):115-118.
    In his article on The Liabilities of Mobility, Merker asserts that “Consciousness presents us with a stable arena for our actions—the world …” and argues for this property as providing evolutionary pressure for the evolution of consciousness. In this commentary, I will explore the implications of Merker’s ideas for consciousness in artificial agents as well as animals, and also meet some possible objections to his evolutionary pressure claim.
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