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Published Articles >> Table of Contents >> Abstract
Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1 (AAMAS'04)
pp. 480-487
Learning User Preferences for Wireless Services Provisioning
G. Lee, Massachusetts Institute of Technology
S. Bauer, Massachusetts Institute of Technology
P. Faratin, Massachusetts Institute of Technology
J. Wroclawski, Massachusetts Institute of Technology
Full Article Text:
 
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AAMAS.2004.10039
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| Abstract |
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The problem of interest is how to dynamically allocate
wireless access services in a competitive market which implements
a take-it-or-leave-it allocation mechanism. In this
paper we focus on the subproblem of preference elicitation,
given a mechanism. The user, due to a number of cognitive
and technical reasons, is assumed to be initially uninformed
over their preferences in the wireless domain. The solution
we have developed is a closed-loop user-agent system that
assists the user in application, task and context dependent
service provisioning by adaptively and interactively learning
to select the best wireless data service. The agent learns
an incrementally revealed user preference model given explicit
or implicit feedback on its decisions by the user. We
model this closed-loop system as a Markov Decision Process,
where the agent actions are rewarded by the user, and
show how a reinforcement learning algorithm can be used
to learn a model of the user’s preferences on-line in the
given allocation mechanism. We evaluate the performance
and value of the agent in a series of preliminary empirical
user studies.
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 Additional Information
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Citation:
G. Lee, S. Bauer, P. Faratin, J. Wroclawski,
"Learning User Preferences for Wireless Services Provisioning,"
aamas,
pp. 480-487,
Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1 (AAMAS'04),
2004
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