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Heekyeong Park - One of the best experts on this subject based on the ideXlab platform.

  • Models of recognition: A review of arguments in favor of a dual-Process account
    Psychonomic Bulletin & Review, 2006
    Co-Authors: Rachel A. Diana, Jason Arndt, Lynne M. Reder, Heekyeong Park
    Abstract:

    The majority of computationally specified models of recognition memory have been based on a single-Process Interpretation, claiming that familiarity is the only influence on recognition. There is increasing evidence that recognition is, in fact, based on two Processes: recollection and familiarity. This article reviews the current state of the evidence for dual-Process models, including the usefulness of the remember/know paradigm, and interprets the relevant results in terms of the source of activation confusion (SAC) model of memory. We argue that the evidence from each of the areas we discuss, when combined, presents a strong case that inclusion of a recollection Process is necessary. Given this conclusion, we also argue that the dual-Process claim that the recollection Process is always available is, in fact, more parsimonious than the single-Process claim that the recollection Process is used only in certain paradigms. The value of a well-specified Process model such as the SAC model is discussed with regard to other types of dual-Process models.

Carter T Butts - One of the best experts on this subject based on the ideXlab platform.

  • a dynamic Process Interpretation of the sparse ergm reference model
    Journal of Mathematical Sociology, 2019
    Co-Authors: Carter T Butts
    Abstract:

    ABSTRACTExponential family random graph models (ERGMs) can be understood in terms of a set of structural biases that act on an underlying reference distribution. This distribution determines many aspects of the behavior and Interpretation of the ERGM families incorporating it. One important innovation in this area has been the development of an ERGM reference model that produces realistic behavior when generalized to sparse networks of varying sizes. Here, we show that this model can be derived from a latent dynamic Process in which tie formation takes place within small local settings between which individuals move. This derivation provides one possible micro-Process Interpretation of the sparse ERGM reference model and sheds light on the conditions under which constant mean degree scaling can emerge.

  • A dynamic Process Interpretation of the sparse ERGM reference model
    The Journal of Mathematical Sociology, 2018
    Co-Authors: Carter T Butts
    Abstract:

    Exponential family random graph models (ERGMs) can be understood in terms of a set of structural biases that act on an underlying reference distribution. This distribution determines many aspects o...

Vladimir S. Jotsov - One of the best experts on this subject based on the ideXlab platform.

  • Discrete Markov Process Interpretation of propositional logic
    2010 5th IEEE International Conference Intelligent Systems, 2010
    Co-Authors: Vassil S. Sgurev, Vladimir S. Jotsov
    Abstract:

    A stochastic Interpretation of propositional logic formulas is introduced that uses a specific discrete Markov Process with two states. The requirements for this Interpretation are formulated. It is shown that the obtained from it stochastic distributions are compatible on a qualitative (probabilistic) level with the respective results of the propositional logic. Examples are presented for usage of this class of Markov Processes and the ways for applying it in artificial intelligence, intelligent systems, expert systems are marked.

  • IEEE Conf. of Intelligent Systems - Discrete Markov Process Interpretation of propositional logic
    2010 5th IEEE International Conference Intelligent Systems, 2010
    Co-Authors: Vassil S. Sgurev, Vladimir S. Jotsov
    Abstract:

    A stochastic Interpretation of propositional logic formulas is introduced that uses a specific discrete Markov Process with two states. The requirements for this Interpretation are formulated. It is shown that the obtained from it stochastic distributions are compatible on a qualitative (probabilistic) level with the respective results of the propositional logic. Examples are presented for usage of this class of Markov Processes and the ways for applying it in artificial intelligence, intelligent systems, expert systems are marked.

Rachel A. Diana - One of the best experts on this subject based on the ideXlab platform.

  • Models of recognition: A review of arguments in favor of a dual-Process account
    Psychonomic Bulletin & Review, 2006
    Co-Authors: Rachel A. Diana, Jason Arndt, Lynne M. Reder, Heekyeong Park
    Abstract:

    The majority of computationally specified models of recognition memory have been based on a single-Process Interpretation, claiming that familiarity is the only influence on recognition. There is increasing evidence that recognition is, in fact, based on two Processes: recollection and familiarity. This article reviews the current state of the evidence for dual-Process models, including the usefulness of the remember/know paradigm, and interprets the relevant results in terms of the source of activation confusion (SAC) model of memory. We argue that the evidence from each of the areas we discuss, when combined, presents a strong case that inclusion of a recollection Process is necessary. Given this conclusion, we also argue that the dual-Process claim that the recollection Process is always available is, in fact, more parsimonious than the single-Process claim that the recollection Process is used only in certain paradigms. The value of a well-specified Process model such as the SAC model is discussed with regard to other types of dual-Process models.

Dorrik A. V. Stow - One of the best experts on this subject based on the ideXlab platform.