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基于ASP的智能空间中上下文感知问题的研究 被引量:1

RESEARCH ON CONTEXT-AWARE IN SMART SPACE BASED ON ANSWER SET PROGRAMMING
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摘要 智能空间和回答集程序ASP的整合解决了智能空间中固定优先关系下的资源冲突问题。然而,智能空间是一个上下文敏感的、动态的环境,随着用户在空间中行为的改变,空间中的信息和服务也要发生动态的变化。原有的基于本体的上下文感知框架仅能实现不同本体信息的推理,而没有考虑环境信息对于上下文感知的影响。为此,基于回答集程序提出一种智能空间中的上下文感知框架,动态感知用户的上下文本体以及环境信息,完成用户在空间中的上下文动态推理。首先,使用本体描述用户的上下文信息;然后使用回答集程序表达上下文推理规则,并引入缺省规则依据本体信息以及环境信息动态决策上下文响应的优先关系;最后,求得回答集程序的解,即为用户上下文事件的决策结果,从而帮助用户实现智能推理。实验结果表明,该框架可以动态决策空间中的优先关系,有效实现空间中的上下文推理。 Integration of Answer Set Programming(ASP) and smart space solves the resource conflict problems in fixed precedence relationship. However,smart space is a context sensitive and dynamic environment. With the change of user's behavior in space,the information and service in the space should also be changed dynamically. The original context-aware framework based on ontology can only implement the reasoning of different ontology information,without considering the influence of environmental information for context-awareness. Thus,a context-aware framework is proposed based on ASP,perceiving the user's context ontology and the environment information dynamically and completing the user's context dynamic reasoning in space. Firstly,the ontology is used to describe the user's context information. Then,ASP is used to express the user's context reason rules in smart space,and default rules is introduced to decide the priority of the dynamic decision context response based ontology and the environment information. Finally,the solution of ASP is obtained,which is the result of the decision of the user's context,so as to help users realize the intelligent reasoning. The experiments show that this framework overcomes dynamic reasoning in space and achieves good effect.
作者 王洁 张婷婷
出处 《计算机应用与软件》 2017年第2期20-26,共7页 Computer Applications and Software
关键词 回答集程序 智能空间 上下文感知 缺省规则 ASP Smart space Context-aware Default rule
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  • 1Ferber J. Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence. Addison-Wesley, 1999.
  • 2Jennings N R, Sycara K, Wooldridge M. A roadmap of agent research and development. Autonomous Agent and Multi-Agent Systems, 1998, 1: 7-38.
  • 3Luo X, Jennings N R, Shadbolt N, Leung H F, Lee J H M. A fuzzy constraint based model for bilateral, multi-issue negotiation in semi-competitive environments. Artificial Intelligence,2003, 148(1-2): 53-102.
  • 4Rao A S, Georgeff M P. BDI agents: From theory to practice.In Proc. the First International Conference on Multi-Agent Systems, San Franciso, CA, USA, 1995, pp.312-319.
  • 5Dix J, Subrahmanian V S. Probabilistic agent programs.ACM Transactions on Computational Logic, 2000, 1(2): 207-245.
  • 6Zhang C, Luo X. An issue on transformation of interval-based uncertainty in distributed expert systems. In Poster Proc. the 10th Australian Joint Conference on Artificial Intelligence,Perth, Australia,1997,pp.38-43.
  • 7He M, Leung H F, Jennings N R. A fuzzy logic based bidding strategy in continuous double auctions. IEEE Transactions on Knowledge and Data Engineering, 2003, 15(6): 1345-1363.
  • 8Wang J, Ju S, Luo X. Probabilistic logic programming with inheritance. In Proc. the 7th and 8th Asian Logic Conferences, World Scientific, Singapore, 2003, pp.409-422.
  • 9Li Y,Zhang C. Information fusion and decision making for utility-based agents. In Proc. the Third World Multi-Conference on Systemic, Cybernetics and Informatics and the Fifth International Conference on Information Systems Analysis and Synthesis, Orlando, USA, 1999, pp.377-384.
  • 10Luo X, Jennings N R, Shadbolt N. Acquiring user tradeoff strategies and preferences for negotiating agents: A defaultthen-adjust method. International Journal of Human Computer Studies, 2006,64(4): 304-321.

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