Skip to main content
SpringerLink
Log in

MAMbO5: a new ontology approach for modelling and managing intelligent virtual environments based on multi-agent systems

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

An intelligent virtual environment simulates a physical world inhabited by autonomous intelligent entities. Multi-agent systems have been usually employed to design systems of this kind. One of the key aspects in the design of intelligent virtual environments is the use of appropriate ontologies which offer a richer and more expressive representation of knowledge. In this sense, this paper proposes an ontology comprising concepts for modelling intelligent virtual environments enhanced with concepts for describing agent-based organisational features. This new ontology, called MAMbO5, is used as an input of the JaCalIVE framework, which is a toolkit for the design and implementation of agent-based intelligent virtual environments.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Notes

  1. Organizational Design of Multi-Agent Systems in the Internet of Things; for further information visit http://ai.foi.hr/oovasis.php.

  2. For further information, please visit: http://talklikeapirate.com/wordpress/.

  3. OWL file available at: http://www.dsic.upv.es/%7ecarrasco/MAMbO5example.owl.

  4. The current version is available at http://www.dsic.upv.es/~carrasco/MAMbO5.owl.

References

  • Ahmed Abbas H (2015) Organization of multi-agent systems: an overview. Int J Intell Inf Syst 4(3):46 (ISSN: 2328-7675)

    Google Scholar 

  • Amiribesheli M, Bouchachia H (2017) A tailored smart home for dementia care. J Ambient Intell Hum Comput 1:1–28 (ISSN: 1868-5137, 1868-5145)

    Google Scholar 

  • Amiribesheli M, Benmansour A, Bouchachia A (2015) A review of smart homes in healthcare. J Ambient Intell Hum Comput 6(4):495–517 (ISSN: 18685145) arXiv: TSMCC.2012.2189204 [10.1109]

    Article  Google Scholar 

  • Barella A, Ricci A, Boissier O, Carrascosa C (2012) MAM5: multi-agent model for intelligent virtual environments. In: 10th European workshop on multi-agent systems (EUMAS 2012), pp 16–30

  • Bordel B (2017) Self-configuration in humanized cyber-physical systems. J Ambient Intell Hum Comput 8(4):485–496 (ISSN: 1868-5137)

    Article  Google Scholar 

  • Chaib A, Boussebough I, Chaoui A (2018) Adaptive service composition in an ambient environment with a multi-agent system. J Ambient Intell Hum Comput 9(2):367–380 (ISSN: 1868-5137)

    Article  Google Scholar 

  • Chen X (2017) A multiagent-based model for pedestrian simulation in subway stations. Simul Modell Pract Theory 71:134–148 (ISSN: 1569-190X)

    Article  Google Scholar 

  • Chen T, Chiu MC (2018) Smart technologies for assisting the life quality of persons in a mobile environment: a review. J Ambient Intell Hum Comput 9(2):319–327 (ISSN: 1868-5137)

    Article  Google Scholar 

  • Corkill DD, Lander SE (1998) Diversity in agent organizations. Obj Mag 8(4):41–47

    Google Scholar 

  • De Wolf T (2004) Emergence and self-organisation: a statement of similarities and differences. In: Proceedings of of the 2nd international workshop on engineering self, pp 96–110

  • Dignum V (2009) The role of organization in agent systems. English. In: Dignum V (ed) Handbook of research on multi-agent systems. Hershey, IGI Global, pp 1–16 (ISBN: 9781605662565)

    Chapter  Google Scholar 

  • Fishwick PA, Miller JA (2004) Ontologies for modeling and simulation: issues and approaches. In: Simulation conference, 2004. Proceedings of the 2004 Winter, vol 1. IEEE

  • Furfaro A (2016) Using virtual environments for the assessment of cybersecurity issues in IoT scenarios. Simul Modell Pract Theory 0:1–12

    Google Scholar 

  • Gabriele D, Ferretti S, Ghini V (2016) Multi-level simulation of Internet of Things on smart territories. Simul Modell Pract Theory 0:1–19

    Google Scholar 

  • Hadfi R, Ito T (2016) Holonic multiagent simulation of complex adaptive systems. In: Javier B (Ed) Highlights of practical applications of scalable multi-agent systems. The PAAMS collection: international workshops of PAAMS 2016, Sevilla, Spain, June 1–3, 2016. Proceedings. Springer, Cham, pp 137–147 (ISBN: 978-3-319-39387-2)

  • Hofmann M, Palii J, Mihelcic G (2011) Epistemic and normative aspects of ontologies in modelling and simulation. J Simul 5(3):135–146

    Article  Google Scholar 

  • Hui TKL, Sherratt RS (2017) Towards disappearing user interfaces for ubiquitous computing: human enhancement from sixth sense to super senses. J Ambient Intell Hum Comput 8(3):449–465 (ISSN: 1868-5137, 1868-5145)

    Article  Google Scholar 

  • Kim S, Lee I (2018) IoT device security based on proxy re-encryption. J Ambient Intell Hum Comput 9(4):1267–1273 (ISSN: 1868-5137, 1868-5145)

    Article  MathSciNet  Google Scholar 

  • Ko E, Kim T, Kim H (2018) Management platform of threats information in IoT environment. J Ambient Intell Hum Comput 9(4):1167–1176 (ISSN: 1868-5137, 1868-5145)

    Article  Google Scholar 

  • Liu Y, Xu C, Zhan Y, Liu Z, Guan J, Zhang H (2017) Incentive mechanism for computation offloading using edge computing: a stackelberg game approach. Comput Netw 129:399–409

    Article  Google Scholar 

  • Liu Y, Bashar AAE, Wu B, Wu H (2018a) Delay-constrained profit maximization for data deposition in mobile opportunistic device-to-device networks. In: 2018 IEEE 19th international symposium on” a world of wireless, mobile and multimedia networks (WoWMoM), IEEE, pp 1–10

  • Liu Y, et al (2018b) Delay-constrained utility maximization for video ads push in mobile opportunistic D2D networks. IEEE Internet Things J

  • Luck M, Aylett R (2000) Applying artificial intelligence to virtual reality: intelligent virtual environments. Appl Artif Intell 14(1):3–32

    Article  Google Scholar 

  • Marcon E (2017) A multi-agent system based on reactive decision rules for solving the caregiver routing problem in home health care. Simul Modell Pract Theory 74:134–151 (ISSN: 1569-190X)

    Article  Google Scholar 

  • Mulero R (2018) Towards ambient assisted cities using linked data and data analysis. J Ambient Intell Hum Comput 9(5):1573–1591 (ISSN: 1868-5137, 1868-5145)

    Article  Google Scholar 

  • Okreša Đ B, Schatten M (2016) Defining ontology combining concepts of massive multi-player online role playing games and organization of large-scale multi-agent systems. In: Opatija HR (ed) 39th international convention on information and communication technology, electronics and microelectronics (MIPRO). IEEE, pp 1330–1335 (ISBN: 978-953-233-086-1)

  • Ricci A, Viroli M, Omicini A (2007) Give agents their artifacts: the A&A approach for engineering working environments in MAS. In: Proceedings of the 6th international joint conference on autonomous agents and multiagent systems, p 150

  • Rincon JA, Carrascosa C, Garcia E (2014) Developing intelligent virtual environments using MAM5 meta-model. In: Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics) 8473 LNAI, pp 379–382 (ISSN: 16113349)

  • Rincon J (2016) Extending MAM5 meta-model and JaCalIV E framework to integrate smart devices from real environments. PLoS One 11:e0149665. https://doi.org/10.1371/journal.pone.0149665

    Article  Google Scholar 

  • Rincon J, Garcia E, Julian V, Carrascosa C (2018) The jacalive framework for mas in IVE: a case study in evolving modular robotics. Neurocomputing 275:608–617

    Article  Google Scholar 

  • Rodriguez S (2011) Holonic multi-agent systems. In: Di Marzo SG, Gleizes MP, Karageorgos A (eds) Natural computing series, natural computing series, vol 37. Springer, Heidelberg, pp 251–279 (ISBN: 978-3-642-17347-9)

    Google Scholar 

  • Samara A, et al. (2017) Affective state detection via facial expression analysis within a human–computer interaction context. J Ambient Intell Hum Comput (ISSN: 1868-5137, 1868-5145)

  • Schatten M (2014) Organizational architectures for large-scale multi-agent systems’ development: an initial ontology. In: Sigeru O, et al (Ed) Advances in intelligent systems and computing, vol 290, pp 261–268

  • Schatten M (2014) Towards a formal conceptualization of organizational design techniques for large scale multi agent systems. Procedia Technol 15:577–586 (ISSN: 22120173)

    Article  Google Scholar 

  • Sharpanskykh A, Treur J (2012) An ambient agent architecture exploiting automated cognitive analysis. J Ambient Intell Hum Comput 3(3):219–237 (ISSN: 1868-5137, 1868-5145)

    Article  Google Scholar 

  • Weyns D, Haesevoets R, Helleboogh A (2010) The MACODO organization model for context-driven dynamic agent organizations. ACM Trans Auton Adapt Syst 5(4):1–29 (ISSN: 15564665)

    Article  Google Scholar 

  • Yang G, Kifer M, Zhao C (2003) Flora-2: a rule-based knowledge representation and inference infrastructure for the semantic web. In: Robert M, Zahir T, Douglas CS (Ed) On the move to meaningful internet systems 2003: CoopIS, DOA, and ODBASE: OTM confederated international conferences, CoopIS, DOA, and ODBASE 2003, Catania, Sicily, Italy, November 3–7, 2003. Proceedings. Springer, Berlin, pp 671–688 (ISBN: 978-3-540-39964-3)

  • Zehe D, et al (2015) SEMSim cloud service: large-scale urban systems simulation in the cloud. In: 58, pp 157–171

Download references

Author information

Authors and Affiliations

  1. Artificial Intelligence Laboratory, Faculty of Organization and Informatics, University of Zagreb, Pavlinska 2, 42000, Varazdin, Croatia

    B. Okreša Ɖurić & M. Schatten

  2. Departamento Sistemas Informáticos y Computación, Universitat Politècnica de València, Valencia, Spain

    J. Rincon, C. Carrascosa & V. Julian

Authors
  1. B. Okreša Ɖurić
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J. Rincon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. C. Carrascosa
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. M. Schatten
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. V. Julian
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to B. Okreša Ɖurić.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This is a collaborative effort of GTI-IA UPV and AI Lab FOI. This work was supported by the project TIN2015-65515-C4-1-R of the Spanish government. This work has been supported in part by the Croatian Science Foundation under the project number 8537.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Okreša Ɖurić, B., Rincon, J., Carrascosa, C. et al. MAMbO5: a new ontology approach for modelling and managing intelligent virtual environments based on multi-agent systems. J Ambient Intell Human Comput 10, 3629–3641 (2019). https://doi.org/10.1007/s12652-018-1089-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-018-1089-4

Keywords

Search

Navigation