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Article Dans Une Revue International Journal of Cognitive Informatics and Natural Intelligence Année : 2010

Giving Personal Assistant Agents a Case-Based Memory

Résumé

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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Dates et versions

hal-00555860 , version 1 (14-01-2011)

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Citer

Kejia Chen, Jean-Paul Barthès. Giving Personal Assistant Agents a Case-Based Memory. International Journal of Cognitive Informatics and Natural Intelligence, 2010, 4 (1), pp.45-64. ⟨10.4018/jcini.2010010103⟩. ⟨hal-00555860⟩
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