UPM Institutional Repository

Improving agent-based meeting scheduling through preference learning.


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


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.

Download File

Full text not available from this repository.
Official URL or Download Paper: http://www.jatit.org

Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
Publisher: Asian Research Publication Network
Keywords: Meeting scheduling; Agent-based negotiation; Negotiation strategy; Back propagation learning method; Neural network.
Depositing User: Ms. Nida Hidayati Ghazali
Date Deposited: 22 Jul 2013 04:56
Last Modified: 22 Jul 2013 04:56
URI: http://psasir.upm.edu.my/id/eprint/15144
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item