The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Giving Personal Assistant Agents a Case-Based Memory
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.
Related Content
|
Hemalatha J. J., Bala Subramanian Chokkalingam, Vivek V., Sekar Mohan.
© 2023.
14 pages.
|
|
R. Muthuselvi, G. Nirmala.
© 2023.
12 pages.
|
|
Jerritta Selvaraj, Arun Sahayadhas.
© 2023.
16 pages.
|
|
Vidhya R., Sandhia G. K., Jansi K. R., Nagadevi S., Jeya R..
© 2023.
8 pages.
|
|
Shanthalakshmi Revathy J., Uma Maheswari N., Sasikala S..
© 2023.
13 pages.
|
|
Uma N. Dulhare, Shaik Rasool.
© 2023.
29 pages.
|
|
R. Nareshkumar, G. Suseela, K. Nimala, G. Niranjana.
© 2023.
22 pages.
|
|
|