Context Modeling Reflecting the Perspectives of Constituent Agents in Distributed Reasoning

Effective manipulation of context is very important in the research of context-awareness. In recent years, thus, a variety of context models have been proposed to properly handle the key aspects of the context, while focusing on scenario-based acquisition, management, and representation of context. However, they are difficult to be employed for agent system requiring distributed reasoning. In this paper we propose a context modeling approach for distributed reasoning and merge operator reflecting the perspective of constituent agents for rational reasoning. In addition, an agent-based context-aware system is developed implementing the proposed scheme. Performance evaluation by computer simulation on a use case of smart classroom shows that the proposed approach enables the agents to rationally reason and thereby provide intelligent context-aware services to the users.