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Using RAAM to model human sequence representation and processing
University of Skövde, School of Humanities and Informatics.
University of Skövde, School of Humanities and Informatics.
2001 (English)Report (Other academic)
Abstract [en]

The human mind has been studied from various perspectives. Some adopt an analytical approach by analyzing humans, yet others attempt to construct automated systems exhibiting certain aspects of mind. Here we argue that connectionist architectures generally fail to exhibit important aspects of mind. We present a number of aspects, relating to human short-term and long-term memory during sequence representation and processing. These aspects are then used as a means to measure the explanatory power of connectionist architectures. We find that connectionist architectures (specifically Recursive Auto-Associative Memories, RAAM) generally fail to model important aspects of the short-term and long-term memory, when representing and processing sequences. Some aspects are correctly modeled, whereas others are modeled incorrectly or it is an open question whether or not they can be modeled at all. From this we go on to present the areas in which more research is needed, before connectionist RAAM-like architectures can be finally claimed to model important aspects of short-term and long-term memory.

Place, publisher, year, edition, pages
Skövde: Institutionen för kommunikation och information , 2001.
Series
IKI Technical Reports, HS-IDA-TR-01-004
Keyword [en]
Recursive Auto-Associative Memory; sequence representation; sequence processing; long-term memory; short-term memory; models of memory
National Category
Information Science
Identifiers
URN: urn:nbn:se:his:diva-1194OAI: oai:DiVA.org:his-1194DiVA: diva2:2322
Available from: 2008-06-17 Created: 2008-06-17 Last updated: 2010-04-01

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
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  • asciidoc
  • rtf