Renewed interest in cognitive information processing has identified the need for novel computing architectures that can efficiently and dynamically support reasoning and learning with emphasis on memory structures. A large number of cognitive processing methods have been implemented in software on conventional computing architectures. This paper describes detailed execution profiling of a particular cognitive method for analogical reasoning called SAGE™. SAGE™ is a symbolic-connectionist, performance oriented analogical reasoner. The primary contribution of the work is to identify the deficiencies and bottlenecks of SAGE™ to inform the development of improved architectures for cognitive information processing, and especially for analogical reasoning.
Performance analysis of a cognitive analogical reasoner
01.03.2009
1265473 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
IEEE | 2007
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