Skip to main content
SpringerLink
Log in

Strategies for contextual reasoning with conflicts in ambient intelligence

  • Regular Paper
  • Published:
Knowledge and Information Systems Aims and scope Submit manuscript

Abstract

Ambient Intelligence environments host various agents that collect, process, change and share the available context information. The imperfect nature of context, the open and dynamic nature of such environments and the special characteristics of ambient agents have introduced new research challenges in the study of Distributed Artificial Intelligence. This paper proposes a solution based on the Multi-Context Systems paradigm, according to which local knowledge of ambient agents is encoded in rule theories (contexts), and information flow between agents is achieved through mapping rules that associate concepts used by different contexts. To resolve potential inconsistencies that may arise from the interaction of contexts through their mappings (global conflicts), we use a preference ordering on the system contexts, which may express the confidence that an agent has in the knowledge imported by other agents. On top of this model, we have developed four alternative strategies for global conflicts resolution, which mainly differ in the type and extent of context and preference information that is used to resolve potential conflicts. The four strategies have been respectively implemented in four versions of a distributed algorithm for query evaluation and evaluated in a simulated P2P system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Adjiman P, Chatalic P, Goasdoue F, Rousset M-C, Simon L (2006) Distributed reasoning in a peer-to-peer setting: application to the semantic web. J Artif Intell Res 25: 269–314

    MATH  MathSciNet  Google Scholar 

  2. Agostini A, Bettini C, Riboni D (2005) Loosely coupling ontological reasoning with an efficient middleware for context-awareness. In: Proceedings of MobiQuitous 2005, pp 175–182

  3. Antoniou G, Billington D, Governatori G, Maher M (2006) Embedding defeasible logic into logic programming. Theory Pract Log Program 6(6): 703–735

    Article  MATH  MathSciNet  Google Scholar 

  4. Antoniou G, Billington D, Governatori G, Maher MJ (2001) Representation results for defeasible logic. ACM Trans Comput Log 2(2): 255–287

    Article  MATH  MathSciNet  Google Scholar 

  5. Bernstein PA, Giunchiglia F, Kementsietsidis A, Mylopoulos J, Serafini L, Zaihrayeu I (2002) Data management for peer-to-peer computing: a vision. In: WebDB, pp 89–94

  6. Bikakis A, Patkos T, Antoniou G, Plexousakis D (2008) A survey of semantics-based approaches for context reasoning in ambient intelligence. In: Mühlhäuser M, Ferscha A, Aitenbichler E (eds) Constructing ambient intelligence, communications in computer and information science. Springer, Berlin, pp 14–23

    Chapter  Google Scholar 

  7. Binas A, McIlraith SA (2007) Exploiting preferences over information sources to efficiently resolve inconsistencies in peer-to-peer query answering. In: AAAI 2007 workshop on preference handling for artificial intelligence

  8. Brewka G, Roelofsen F, Serafini L (2007) Contextual default reasoning. In: IJCAI, pp 268–273

  9. Buvac S, Mason IA (1993) Propositional logic of context. In: AAAI, pp 412–419

  10. Calvanese D, De Giacomo G, Lembo D, Lenzerini M, Rosati R (2005) Inconsistency tolerance in P2P data integration: an epistemic logic approach. In: DBPL-05, 3774 of LNCS, SV, pp 90–105

  11. Calvanese D, De Giacomo G, Lenzerini M, Rosati R (2004) Logical foundations of peer-to-peer data integration. ACM, New york, pp 241–251

  12. Casali A, Godo L, Sierra C (2008) A logical framework to represent and reason about graded preferences and intentions. In: KR, pp 27–37

  13. Chatalic P, Nguyen GH, Rousset M-C (2006) Reasoning with inconsistencies in propositional peer-to-peer inference systems. In: ECAI, pp 352–356

  14. Chen H, Finin T, Joshi A (2003) Semantic web in a pervasive context-aware architecture. Artif Intell Mob Syst 2003, 33–40

  15. Cristani M, Burato E (2009) Approximate solutions of moral dilemmas in multiple agent system. Knowl Inf Syst 18(2): 157–181

    Article  Google Scholar 

  16. Dastani M, Governatori G, Rotolo A, Song I, van der Torre L (2007) Contextual deliberation of cognitive agents in defeasible logic. In: AAMAS, p 148

  17. Forstadius J, Lassila O, Seppanen T (2005) RDF-based model for context-aware reasoning in rich service environment. In: PerCom 2005 workshops, pp 15–19

  18. Franconi E, Kuper GM, Lopatenko A, Serafini L (2003) A robust logical and computational characterisation of peer-to-peer database systems. In: DBISP2P, pp 64–76

  19. Gandon FL, Sadeh NM (2004) Semantic web technologies to reconcile privacy and context awareness. J Web Semant 1: 241–260

    Google Scholar 

  20. Ghidini C, Giunchiglia F (2001) Local models semantics, or contextual reasoning = locality + compatibility. Artif Intell 127(2): 221–259

    Article  MATH  MathSciNet  Google Scholar 

  21. Giunchiglia F, Serafini L (1994) Multilanguage hierarchical logics, or: how we can do without modal logics. Artif Intell 65(1): 29–70

    Article  MATH  MathSciNet  Google Scholar 

  22. Gong L (2001) JXTA: a network programming environment. IEEE Internet Comput 5(3): 88–95

    Article  Google Scholar 

  23. Governatori G, Maher MJ, Antoniou G, Billington D (2004) Argumentation semantics for defeasible logic. J Log Comput 14(5): 675–702

    Article  MATH  MathSciNet  Google Scholar 

  24. Gu T, Pung HK, Zhang DQ (2004) A middleware for building context-aware mobile services. In: Proceedings of the IEEE vehicular technology conference (VTC 2004). Milan, Italy

  25. Halevy AY, Ives ZG, Suciu D, Tatarinov I (2003) Schema mediation in peer data management Systems. In: ICDE, p 505

  26. Hatala M, Wakkary R, Kalantari L (2005) Ontologies and rules in support of real-time ubiquitous application. J Web Semant, Special Issue on “Rules and ontologies for Semantic Web” 3(1) 5–22 (2004)

    Google Scholar 

  27. Henricksen K, Indulska J (2004) Modelling and using imperfect context information. In: Proceedings of PERCOMW ’04’. IEEE Computer Society, Washington, DC, pp. 33–37

  28. Khushraj D, Lassila O, Finin T (2004) sTuples: semantic tuple spaces. In: First annual international conference on mobile and Ubiquitous systems: networking and services (MobiQuitousć604), pp 267–277

  29. Kofod-Petersen A, Mikalsen M (2005) Representing and reasoning about context in a mobile environment. Revue d’Intelligence Artificielle 19(3): 479–498

    Article  Google Scholar 

  30. Korpipaa P, Mantyjarvi J, Kela J, Keranen H, Malm E-J (2003) Managing context information in mobile devices. IEEE Pervasive Comput 02(3): 42–51

    Article  Google Scholar 

  31. Krummenacher R, Kopecký J, Strang T (2005) Sharing context information in semantic spaces. In: OTM workshops, pp 229–232

  32. Maher MJ (2002) A model-theoretic semantics for defeasible Logic. In: Paraconsistent computational logic, pp 67–80

  33. McCarthy J (1987) Generality in artificial intelligence. Commun ACM 30(12): 1030–1035

    Article  MATH  MathSciNet  Google Scholar 

  34. McCarthy J, Buvač S (1998) Formalizing context expanded notes. In: Aliseda A, Glabbeek R, Westerståhl D (eds) Computing natural language. CSLI Publications, Stanford California, pp 13–50

    Google Scholar 

  35. Nguyen NT, Katarzyniak R (2009) Actions and social interactions in multi-agent systems. Knowl Inf Syst 18(2): 133–136

    Article  Google Scholar 

  36. Nute D (1997) Defeasible deontic logic. Kluwer, Chapter Apparent Obligation, pp 288–315

  37. Nute D (2001) Defeasible logic. In: Proceedings of the 14th international conference on applications of Prolog, pp 87–114

  38. Patkos T, Bikakis A, Antoniou G, Plexousakis D, Papadopouli M (2007) A semantics-based framework for context-aware services: lessons learned and challenges. In: Proceedings of 4th international conference on Ubiquitous intelligence and computing (UIC-2007), Vol. 4611 of LNCS, Springer, pp 839–848

  39. Ranganathan A, Campbell RH (2003) An infrastructure for context-awareness based on first order logic. Pers Ubiquitous Comput 7(6): 353–364

    Article  Google Scholar 

  40. Resconi G, Kovalerchuk B (2009) Agents’ model of uncertainty. Knowl Inf Syst 18(2): 213–229

    Article  Google Scholar 

  41. Roelofsen F, Serafini L (2005) Minimal and absent information in contexts. In: IJCAI, pp 558–563

  42. Sabater J, Sierra C, Parsons S, Jennings NR (2002) Engineering executable agents using multi-context systems. J Log Comput 12(3): 413–442

    Article  MATH  MathSciNet  Google Scholar 

  43. Serafini L, Bouquet P (2004) Comparing formal theories of context in AI. Artif Intell 155(1–2): 41–67

    Article  MATH  MathSciNet  Google Scholar 

  44. Sinner A, Kleemann T, von Hessling A (2004) Semantic user profiles and their applications in a mobile environment. In: Artificial intelligence in mobile systems 2004

  45. Toninelli A, Montanari R, Kagal L, Lassila O (2006) A semantic context-aware access control framework for secure collaborations in pervasive computing environments. In: Proceedings of 5th international semantic web conference, pp 5–9

  46. Turhan A-Y, Springer T, Berger M (2006) Pushing doors for modeling contexts with OWL DL a case study. In: ‘PERCOMW ’06: Proceedings of the 4th annual IEEE international conference on Pervasive Computing and Communications Workshops’, IEEE Computer Society, Washington, DC

  47. Wang XH, Dong JS, Chin CY, Hettiarachchi SR, Zhang D (2004) Semantic space: an infrastructure for smart spaces. IEEE Pervasive Comput 3(3): 32–39

    Article  Google Scholar 

  48. Wang XH, Zhang DQ, Gu T, Pung HK (2004) Ontology based context modeling and reasoning using OWL. In: ‘PERCOMW ’04: proceedings of the second IEEE Annual conference on pervasive computing and communications workshops’, IEEE Computer Society, Washington, DC, p 18

Download references

Author information

Authors and Affiliations

  1. Institute of Computer Science, FO.R.T.H., Crete, Greece

    Antonis Bikakis & Grigoris Antoniou

  2. Department of Informatics, Athens University of Economics and Business, Athens, Greece

    Panayiotis Hasapis

Authors
  1. Antonis Bikakis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Grigoris Antoniou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Panayiotis Hasapis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Antonis Bikakis.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bikakis, A., Antoniou, G. & Hasapis, P. Strategies for contextual reasoning with conflicts in ambient intelligence. Knowl Inf Syst 27, 45–84 (2011). https://doi.org/10.1007/s10115-010-0293-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10115-010-0293-0

Keywords

Search

Navigation