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Neeraj Arora

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Neeraj Arora

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Publications by Neeraj Arora (bibliography)

» 1998 «

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Sen, Sandip, Arora, Neeraj and Roychowdhury, Shounak (1998): Using Limited Information to Enhance Group Stability. In International Journal of Human-Computer Studies, 48 (1) pp. 69-82

“The performance of individual agents in a group depends critically on the quality of information available to them about local and global goals and resources. In general, it is assumed that the more accurate and comprehensive the available information, the better is the expected performance of the individual and the group. This conclusion can be challenged in a number of scenarios. We investigate the use of limited information by agents in choosing between one of several different options, and conclude that if agents are kept ignorant about, or they deliberately ignore, any number of options, the group can converge faster to a stable and optimal configuration. We present a probabilistic analysis that sheds light on the observed phenomenon of quicker system convergence with less global information. This analysis suggests a desirable adaptive behavior on the part of individual agents. Experiments with agents following these adaptive behavior exhibits faster convergence. We also demonstrate how a couple of coalition formation schemes can improve the rate of convergence. A variable coalition formation mechanism is found to be more effective than a static one.”

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» 1997 «

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Sen, Sandip, Haynes, Thomas and Arora, Neeraj (1997): Satisfying User Preferences while Negotiating Meetings. In International Journal of Human-Computer Studies, 47 (3) pp. 407-427

“Our research agenda focuses on building software agents that can facilitate and streamline group problem solving in organizations. We are particularly interested in developing intelligent agents that can partially automate routine information processing tasks by representing and reasoning with the preferences and biases of associated users. The distributed meeting scheduler is a collection of agents, responsible for scheduling meetings for their respective users. Users have preferences on when they like to meet, e.g. time of day, day of week, status of other invitees, topic of the meeting, etc. The agent must balance such concerns, proposing and accepting meeting times that satisfy as many of these criteria as possible. For example, a user might prefer not to meet at lunchtime unless the president of the company is hosting the meeting. We apply techniques from voting theory to arrive at consensus choices for meeting times while balancing different preferences.”

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