Improving agent-based meeting scheduling through preference learning.
This paper presented an autonomous Secretary Agent (SA) that can perform meeting scheduling task on behalf of their respective user through negotiations. Previous study of searching strategy uses relaxation process to allow agents negotiate by relaxing their preference when conflict arises. However...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Asian Research Publication Network
2009
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| _version_ | 1825945564383019008 |
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| author | Sulaiman, Md. Nasir Tang, En Lai Selamat, Mohd Hasan Muda , Zaiton |
| author_facet | Sulaiman, Md. Nasir Tang, En Lai Selamat, Mohd Hasan Muda , Zaiton |
| author_sort | Sulaiman, Md. Nasir |
| collection | UPM |
| description | This paper presented an autonomous Secretary Agent (SA) that can perform meeting scheduling task on behalf of their respective user through negotiations. Previous study of searching strategy uses relaxation process to allow agents negotiate by relaxing their preference when conflict arises.
However, this increased the cost of searching process. As a result, an improvement of relaxation searching strategy by adapting Neural Network (NN) learning mechanism is proposed. The back-propagation learning method is used
in this research to intelligently predict the participants’
preferences and guide the host in selecting proposal
s that are more likely to get accepted. Hence, higher quality solution can be found in lower communication cost. The comparison result between the proposed and two previous estimation strategies showed improvement of quality of the
solution as well as the communication cost of the proposed strategy. |
| first_indexed | 2024-03-06T07:33:28Z |
| format | Article |
| id | upm.eprints-15144 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T07:33:28Z |
| publishDate | 2009 |
| publisher | Asian Research Publication Network |
| record_format | dspace |
| spelling | upm.eprints-151442013-07-22T04:56:32Z http://psasir.upm.edu.my/id/eprint/15144/ Improving agent-based meeting scheduling through preference learning. Sulaiman, Md. Nasir Tang, En Lai Selamat, Mohd Hasan Muda , Zaiton This paper presented an autonomous Secretary Agent (SA) that can perform meeting scheduling task on behalf of their respective user through negotiations. Previous study of searching strategy uses relaxation process to allow agents negotiate by relaxing their preference when conflict arises. However, this increased the cost of searching process. As a result, an improvement of relaxation searching strategy by adapting Neural Network (NN) learning mechanism is proposed. The back-propagation learning method is used in this research to intelligently predict the participants’ preferences and guide the host in selecting proposal s that are more likely to get accepted. Hence, higher quality solution can be found in lower communication cost. The comparison result between the proposed and two previous estimation strategies showed improvement of quality of the solution as well as the communication cost of the proposed strategy. Asian Research Publication Network 2009 Article PeerReviewed Sulaiman, Md. Nasir and Tang, En Lai and Selamat, Mohd Hasan and Muda , Zaiton (2009) Improving agent-based meeting scheduling through preference learning. Journal of Theoretical and Applied Information Technology, 6 (2). pp. 155-164. ISSN 1992-8645 http://www.jatit.org English |
| spellingShingle | Sulaiman, Md. Nasir Tang, En Lai Selamat, Mohd Hasan Muda , Zaiton Improving agent-based meeting scheduling through preference learning. |
| title | Improving agent-based meeting scheduling through preference learning. |
| title_full | Improving agent-based meeting scheduling through preference learning. |
| title_fullStr | Improving agent-based meeting scheduling through preference learning. |
| title_full_unstemmed | Improving agent-based meeting scheduling through preference learning. |
| title_short | Improving agent-based meeting scheduling through preference learning. |
| title_sort | improving agent based meeting scheduling through preference learning |
| work_keys_str_mv | AT sulaimanmdnasir improvingagentbasedmeetingschedulingthroughpreferencelearning AT tangenlai improvingagentbasedmeetingschedulingthroughpreferencelearning AT selamatmohdhasan improvingagentbasedmeetingschedulingthroughpreferencelearning AT mudazaiton improvingagentbasedmeetingschedulingthroughpreferencelearning |