Conflict Resolution and Preference Learning in Ubiquitous Environment.pdfVIP

Conflict Resolution and Preference Learning in Ubiquitous Environment Md. Kamrul Hasan, Kim Anh, Lenin Mehedy, Young-Koo Lee, Sungyoung Lee1 Real-Time MultiMedia Lab, Department of Computer Engineering, Kyung Hee University, 449-701, Republic of Korea {kamrul, anhpnk, lenin}oslab.khu.ac.kr, yklee@khu.ac.kr, sylee@oslab.khu.ac.kr Abstract. Building intelligent environment is one of crucial challenges for ubiquitous computing developers. To make the environment adapt rationally according to the desire of users, the system should be able to guess users’ interest, by learning users’ behavior, habit or preference. While learning the user preference, dealing with uncertainty and conflict resolution is of the utmost importance. When many users are involved in a ubiquitous environment, the decisions of one user can be affected by the desires of others. This makes learning and prediction of user preference difficult. To address the issue, we propose an approach of user preference learning which can be used widely in context-aware systems. We use Bayesian RN-Metanetwork, a multilevel Bayesian network to model user preference and priority. Keyword: Conflict resolution, preference learning, Bayesian network, Bayesian RN-Metanetwork, context awareness. 1 Introduction Ubiquitous computing is mainly about building systems which are useful to users, which ...weave themselves into the fabric of everyday life until they are indistinguishable from it [1]. Users tend to move around often, doing new things, visiting new places, changing their minds suddenly, and changing their moods, too. Therefore, a helpful system should react according to the changing context of the user. Absorbing and developing the key ideas of ubiquitous computing as well as context- awareness, a smart environment (e.g. smart office, smart home) contains a large number of invisible sensors and actuators which enable the system to “think and work” based on its own perception of users