Personalized Content Representation through Hybridization of Mobile Agent and Interface Agent

Abstract

Mobile agent has an ability to co-operate with heterogeneous network environment. There are specific predefined techniques to impart mobility to an agent. As a result, the agent behaves only in predefined way. To impart other features beside mobility that helps in interfacing the destination network to complete the intended job, a mobile agent need to be incorporated with additional functionalities. One of such functionalities is ability to access local user profiles, preferences, and other resources as well as other local agents to present information in user’s context. To meet this demand, hybridization of mobile and interface agent that facilitates development of customized application is discussed in this chapter. The multi-agent architecture, described in this chapter, encompasses this hybrid agent to access user profile and fuzzy indicator matrix. Both the profile and matrix are further utilized to construct content preference list according to users’ perspectives. The indicator matrix enlists typical interest and preferences of a group, such as purpose of surfing/using the system (research, teaching, learning, problem solving, etc.); level information needed (highly technical, conceptual, mixed, etc.), media preference (type of document such as text, code, video, etc.). The system is designed as multi-tier structure called resource tier, service tier, and application tier to provide resources, third party services, and application support to learners, instructors, and administrator groups. The chapter utilizes the proposed generic multi tier architecture for a personalized learning (p-Learning) system and discusses its design in detail including working of different agents, mobility and ticket management, user profile structure, and risk management policies. The chapter concludes with discussion on results and future research directions.