10 found
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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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  2.  33
    A Connectionist Approach to Knowledge Representation and Limited Inference.Lokendra Shastri - 1988 - Cognitive Science 12 (3):331-392.
    Although the connectionist approach has lead to elegant solutions to a number of problems in cognitive science and artificial intelligence, its suitability for dealing with problems in knowledge representation and inference has often been questioned. This paper partly answers this criticism by demonstrating that effective solutions to certain problems in knowledge representation and limited inference can be found by adopting a connectionist approach. The paper presents a connectionist realization of semantic networks, that is, it describes how knowledge about concepts, their (...)
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  3.  7
    Default reasoning in semantic networks: A formalization of recognition and inheritance.Lokendra Shastri - 1989 - Artificial Intelligence 39 (3):283-355.
  4.  82
    Temporal synchrony, dynamic bindings, and Shruti: A representational but nonclassical model of reflexive reasoning.Lokendra Shastri - 1996 - Behavioral and Brain Sciences 19 (2):331-337.
    Lange & Dyer misunderstand what is meant by an “entity” and confuse a medium of representation with the content being represented. This leads them to the erroneous conclusion that SHRUTI will run out of phases and that its representation of bindings lacks semantic content. It is argued that the limit on the number of phases suffices, and SHRUTI can be interpreted as using “dynamic signatures” that offer significant advantages over fixed preexisting signatures. Bonatti refers to three levels of commitment to (...)
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  5.  43
    From transient patterns to persistent structure: A model of episodic memory formation via cortico-hippocampal interactions.Lokendra Shastri - forthcoming - Behavioral and Brain Sciences.
  6. Connectionism.Jerome A. Feldman & Lokendra Shastri - 2003 - In L. Nadel (ed.), Encyclopedia of Cognitive Science. Nature Publishing Group.
     
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  7.  31
    An extended local connectionist manifesto: Embracing relational and procedural knowledge.Lokendra Shastri - 2000 - Behavioral and Brain Sciences 23 (4):492-493.
    Page has performed an important service by dispelling several myths and misconceptions concerning the localist approach. The localist position and computational model presented in the target article, however, are overly restrictive and do not address the representation of complex conceptual items such as events, situations, actions, and plans. Working toward the representation of such items leads to a more sophisticated and articulated view of the localist approach.
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  8.  32
    A step toward modeling reflexive reasoning.Lokendra Shastri & Venkat Ajjanagadde - 1993 - Behavioral and Brain Sciences 16 (3):477-494.
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  9.  45
    Comparing the neural blackboard and the temporal synchrony-based SHRUTI architectures.Lokendra Shastri - 2006 - Behavioral and Brain Sciences 29 (1):84-86.
    Contrary to the assertions made in the target article, temporal synchrony, coupled with an appropriate choice of representational primitives, leads to a functionally adequate and neurally plausible architecture that addresses the massiveness of the binding problem, the problem of 2, the problem of variables, and the transformation of activity-based transient representations of events and situations into structure-based persistent encodings of the same.
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  10. Spreading‐Activation Networks.Lokendra Shastri - 2003 - In L. Nadel (ed.), Encyclopedia of Cognitive Science. Nature Publishing Group.
     
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