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  1. From simple associations to systematic reasoning: A connectionist representation of rules, variables, and dynamic binding using temporal synchrony.Lokendra Shastri & Venkat Ajjanagadde - 1993 - Behavioral and Brain Sciences 16 (3):417-51.
    Human agents draw a variety of inferences effortlessly, spontaneously, and with remarkable efficiency – as though these inferences were a reflexive response of their cognitive apparatus. Furthermore, these inferences are drawn with reference to a large body of background knowledge. This remarkable human ability seems paradoxical given the complexity of reasoning reported by researchers in artificial intelligence. It also poses a challenge for cognitive science and computational neuroscience: How can a system of simple and slow neuronlike elements represent a large (...)
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  • A logic for reasoning about ambiguity.Joseph Y. Halpern & Willemien Kets - 2014 - Artificial Intelligence 209 (C):1-10.
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  • (1 other version)Speeding up problem solving by abstraction: a graph oriented approach.R. C. Holte, T. Mkadmi, R. M. Zimmer & A. J. MacDonald - 1996 - Artificial Intelligence 85 (1-2):321-361.
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  • (1 other version)Race‐Based Parsing and Syntactic Disambiguation.Susan Weber McRoy & Graeme Hirst - 1990 - Cognitive Science 14 (3):313-353.
    We present a processing model that integrates same important psychological claims about the human sentence‐parsing mechanism: namely, that processing is influenced by limitations an working memory and by various syntactic preferences. The model uses time‐constraint information to resolve conflicting preferences in a psychologically plausible way. The starting paint far this proposal is the Sausage Machine model (Fodor & Frazier, 1980: Frazier & Fodor, 1978). From there, we attempt to overcome the original model's dependence an ad hoc aspects of its grammar, (...)
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  • Episodic logic: A comprehensive, natural representation for language understanding. [REVIEW]Chung Hee Hwang & Lenhart K. Schubert - 1993 - Minds and Machines 3 (4):381-419.
    A new comprehensive framework for narrative understanding has been developed. Its centerpiece is a new situational logic calledEpisodic Logic, a knowledge and semantic representation well-adapted to the interpretive and inferential needs of general NLU. The most distinctive features of EL is its natural language-like expressiveness. It allows for generalized quantifiers, lambda abstraction, sentence and predicate modifiers, sentence and predicate reification, intensional predicates, unreliable generalizations, and perhaps most importantly, explicit situational variables linked to arbitrary formulas that describe them. These allow episodes (...)
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  • (1 other version)Race‐Based Parsing and Syntactic Disambiguation.Susan Weber McRoy & Graeme Hirst - 1990 - Cognitive Science 14 (3):313-353.
    We present a processing model that integrates same important psychological claims about the human sentence‐parsing mechanism: namely, that processing is influenced by limitations an working memory and by various syntactic preferences. The model uses time‐constraint information to resolve conflicting preferences in a psychologically plausible way. The starting paint far this proposal is the Sausage Machine model (Fodor & Frazier, 1980: Frazier & Fodor, 1978). From there, we attempt to overcome the original model's dependence an ad hoc aspects of its grammar, (...)
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  • Existence assumptions in knowledge representation.Graeme Hirst - 1991 - Artificial Intelligence 49 (1-3):199-242.
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