Reflecting the Perspectives of Multiple Agents in Distributed Reasoning for Context-Aware Service

Abstract Effective manipulation of context is very important in providing the context-aware services. In recent years, 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 the agent-based 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.

[1]  Daqiang Zhang,et al.  Future Generation Computer Systems Context Reasoning Using Extended Evidence Theory in Pervasive Computing Environments , 2022 .

[2]  Zakaria Maamar,et al.  Toward Virtual Marketplaces for E-Commerce Support , 2001, CACM.

[3]  Jadwiga Indulska,et al.  Developing context-aware pervasive computing applications: Models and approach , 2006, Pervasive Mob. Comput..

[4]  Hee Yong Youn,et al.  Modeling and Verification of Context-Awareness Service for Time Critical Applications Using Colored Petri-Net , 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[5]  Sajal K. Das,et al.  Supporting pervasive computing applications with active context fusion and semantic context delivery , 2010, Pervasive Mob. Comput..

[6]  Stathes Hadjiefthymiades,et al.  Enhancing Situation-Aware Systems through Imprecise Reasoning , 2008, IEEE Transactions on Mobile Computing.

[7]  Fang Dong,et al.  A context-aware personalized resource recommendation for pervasive learning , 2010, Cluster Computing.

[8]  Frank Dürr,et al.  A System for Distributed Context Reasoning , 2010, 2010 Sixth International Conference on Autonomic and Autonomous Systems.

[9]  Anind K. Dey,et al.  Understanding and Using Context , 2001, Personal and Ubiquitous Computing.

[10]  Hee Yong Youn,et al.  A Flexible and Scalable Agent Platform for Multi-Agent Systems , 2007 .

[11]  Euiho Suh,et al.  Context-aware system for proactive personalized service based on context history , 2009, Expert Syst. Appl..

[12]  J. Blanc,et al.  Fusion of expert knowledge with data using belief functions: a case study in waste-water treatment , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).

[13]  Hee Yong Youn,et al.  Prediction-Based Dynamic Thread Pool Management of Agent Platform for Ubiquitous Computing , 2007, UIC.

[14]  M. Kang,et al.  An Agent-Based Context-Aware Middleware for Pervasive Computing , 2008, 2008 International Symposium on Information Science and Engineering.

[15]  Hee Yong Youn,et al.  Hierarchical P2P Networking and Two-level Compression Scheme for Multi-agent System Supporting Context-aware Applications , 2009 .

[16]  NICHOLAS R. JENNINGS,et al.  An agent-based approach for building complex software systems , 2001, CACM.

[17]  Grigoris Antoniou,et al.  Distributed Defeasible Contextual Reasoning in Ambient Computing , 2008, AmI.

[18]  Hee Yong Youn,et al.  Modeling and Analysis of Time-Critical Context-Aware Service Using Extended Interval Timed Colored Petri Nets , 2012, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[19]  Javier García,et al.  A QoS Control Mechanism to Provide Service Differentiation and Overload Protection to Internet Scalable Servers , 2009, IEEE Transactions on Services Computing.

[20]  Marinus Maris,et al.  A multi-agent systems approach to distributed bayesian information fusion , 2010, Inf. Fusion.

[21]  José M. Tribolet,et al.  A 'context-aware' and agent-centric perspective for the alignment between individuals and organizations , 2010, Inf. Syst..

[22]  Mahadev Satyanarayanan Challenges in Implementing a Context-Aware System , 2002 .

[23]  Nicolas Lhuillier,et al.  FOUNDATION FOR INTELLIGENT PHYSICAL AGENTS , 2003 .

[24]  Hee Yong Youn,et al.  Context-based Dynamic Channel Management for Efficient Event Service in Pervasive Computing , 2007 .

[25]  Carl K. Chang,et al.  Situ: A Situation-Theoretic Approach to Context-Aware Service Evolution , 2009, IEEE Transactions on Services Computing.

[26]  Michael Luck,et al.  Agent technology: Enabling next generation computing , 2003 .

[27]  Hee Yong Youn,et al.  A New Agent Platform Architecture Supporting the Agent Group Paradigm for Multi-Agent Systems , 2007 .

[28]  H. Kawashima,et al.  A Distributed Inference System on Sensor Nodes using Neighbors' Context Data , 2007, 2007 IEEE International Workshop on Databases for Next Generation Researchers.

[29]  Dazhou Kang,et al.  Distributed Reasoning with Fuzzy Description Logics , 2007, International Conference on Computational Science.

[30]  Chun-Yi Wu,et al.  Application of context-aware and personalized recommendation to implement an adaptive ubiquitous learning system , 2011, Expert Syst. Appl..

[31]  Petteri Nurmi Reasoning in Context-Aware Systems , 2004 .

[32]  Filip De Turck,et al.  Distributed Reasoning for Context-Aware Services through Design of an OWL Meta-Model , 2008, Fourth International Conference on Autonomic and Autonomous Systems (ICAS'08).

[33]  Victor R. Lesser,et al.  A survey of multi-agent organizational paradigms , 2004, The Knowledge Engineering Review.

[34]  Mel Siegel,et al.  Sensor data fusion for context-aware computing using dempster-shafer theory , 2004 .

[35]  Arkady B. Zaslavsky,et al.  Multiple-Agent Perspectives in Reasoning About Situations for Context-Aware Pervasive Computing Systems , 2008, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.