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Giving Personal Assistant Agents a Case-Based Memory

Giving Personal Assistant Agents a Case-Based Memory

Ke-Jia Chen, Jean-Paul A. Barthès
Copyright: © 2010 |Volume: 4 |Issue: 1 |Pages: 20
ISSN: 1557-3958|EISSN: 1557-3966|ISSN: 1557-3958|EISBN13: 9781616929312|EISSN: 1557-3966|DOI: 10.4018/jcini.2010010103
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MLA

Chen, Ke-Jia, and Jean-Paul A. Barthès. "Giving Personal Assistant Agents a Case-Based Memory." IJCINI vol.4, no.1 2010: pp.45-64. http://doi.org/10.4018/jcini.2010010103

APA

Chen, K. & Barthès, J. A. (2010). Giving Personal Assistant Agents a Case-Based Memory. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 4(1), 45-64. http://doi.org/10.4018/jcini.2010010103

Chicago

Chen, Ke-Jia, and Jean-Paul A. Barthès. "Giving Personal Assistant Agents a Case-Based Memory," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) 4, no.1: 45-64. http://doi.org/10.4018/jcini.2010010103

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Abstract

We consider Personal Assistant (PA) agents as cognitive agents capable of helping users handle tasks at their workplace. A PA must communicate with the user using casual language, sub-contract the requested tasks, and present the results in a timely fashion. This leads to fairly complex cognitive agents. However, in addition, such an agent should learn from previous tasks or exchanges, which will increase its complexity. Learning requires a memory, which leads to the two following questions: Is it possible to design and build a generic model of memory? If it is, is it worth the trouble? The article tries to answer the questions by presenting the design and implementation of a memory for PA agents, using a case approach, which results in an improved agent model called MemoPA.

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