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Modelling Situation-Aware Formalism Using BDI Reasoning Agents

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Context-Aware Systems and Applications, and Nature of Computation and Communication (ICCASA 2020, ICTCC 2020)

Abstract

Natural or man-made disasters are unavoidable situations that can occur anytime and anywhere. Timely disaster response plays a vital role in reducing its after-effects and can save countless lives. Over the years, people have been developing the guidelines and processes to cope up with such kinds of hazardous situations. In recent years, situation-awareness has been considered to be the most fascinating approach for the situation assessment and provides decision support accordingly. Situation-aware systems observe/perceive dynamic changes in the environment, understand/comprehend the situation, and perform actions according to the environment. Although state-of-the-art formalisms have been developed to handle such kinds of hazardous situations intelligently and rescue the victims. However, there are still many uncontrolled challenging issues. In this paper, we present a Belief-Desire-Intention (BDI) based multi-agent formalism to model the context-aware decision support system dynamically in order to achieve the desired goals. To illustrate the use of the proposed formalism, we develop a simple case study in which BDI agents are modeled and simulated to present results in terms of agents’ reasoning processes. The behavior of the system has been tested using the NetLogo simulation environment to rigorously evaluate the validity of the system.

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References

  1. Akhtar, S.M., Nazir, M., Saleem, K., Haque, H.M.U., Hussain, I.: An ontology-driven IoT based healthcare formalism. Int. J. Adv. Comput. Sci. Appl 11(2), 479–486 (2020)

    Google Scholar 

  2. Alkhomsan, M.N., Hossain, M.A., Rahman, S.M.M., Masud, M.: Situation awareness in ambient assisted living for smart healthcare. IEEE Access 5, 20716–20725 (2017)

    Article  Google Scholar 

  3. Boril, J., Smrz, V., Mach, O.: Development of experimental methods for testing of human performance in the framework of future millitary pilot’s preparation. In: 2017 International Conference on Military Technologies (ICMT), pp. 548–552. IEEE (2017)

    Google Scholar 

  4. Buettner, R., Baumgartl, H.: A highly effective deep learning based escape route recognition module for autonomous robots in crisis and emergency situations. In: Proceedings of the 52nd Hawaii International Conference on System Sciences (2019)

    Google Scholar 

  5. Caillou, P., Gaudou, B., Grignard, A., Truong, C.Q., Taillandier, P.: A simple-to-use BDI architecture for agent-based modeling and simulation. In: Jager, W., Verbrugge, R., Flache, A., de Roo, G., Hoogduin, L., Hemelrijk, C. (eds.) Advances in Social Simulation 2015. AISC, vol. 528, pp. 15–28. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-47253-9_2

    Chapter  Google Scholar 

  6. Chen, H., Tolia, S.: Steps towards creating a context-aware software agent system. HP. Technical report HPL-2001-231 (2001)

    Google Scholar 

  7. Endsley, M.R., Garland, D.J.: Pilot situation awareness training in general aviation. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 44, pp. 357–360. SAGE Publications, Los Angeles (2000)

    Google Scholar 

  8. Evertsz, R., Thangarajah, J., Ly, T.: A BDI-based methodology for eliciting tactical decision-making expertise. In: Sarker, R., Abbass, H.A., Dunstall, S., Kilby, P., Davis, R., Young, L. (eds.) Data and Decision Sciences in Action. LNMIE, pp. 13–26. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-55914-8_2

    Chapter  Google Scholar 

  9. Feng, Y.H., Teng, T.H., Tan, A.H.: Modelling situation awareness for context-aware decision support. Expert Syst. Appl. 36(1), 455–463 (2009)

    Article  Google Scholar 

  10. Georgeff, M., Pell, B., Pollack, M., Tambe, M., Wooldridge, M.: The belief-desire-intention model of agency. In: Müller, J.P., Rao, A.S., Singh, M.P. (eds.) ATAL 1998. LNCS, vol. 1555, pp. 1–10. Springer, Heidelberg (1999). https://doi.org/10.1007/3-540-49057-4_1

    Chapter  Google Scholar 

  11. Junger, D., Guinelli, J., Pantoja, C.E.: An analysis of Javino middleware for robotic platforms using Jason and JADE frameworks. In: 10th Software Agents, Environments and Applications School (2016)

    Google Scholar 

  12. Little, B.: The deadliest earthquake ever recorded (2020). https://www.history.com/news/the-deadliest-earthquake-ever-recorded

  13. Ramirez, W.A.L., Fasli, M.: Integrating NetLogo and Jason: a disaster-rescue simulation. In: 2017 9th Computer Science and Electronic Engineering (CEEC), pp. 213–218. IEEE (2017)

    Google Scholar 

  14. Luna Ramirez, W.A., Fasli, M.: Plan acquisition in a BDI agent framework through intentional learning. In: Berndt, J.O., Petta, P., Unland, R. (eds.) MATES 2017. LNCS (LNAI), vol. 10413, pp. 167–186. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-64798-2_11

    Chapter  Google Scholar 

  15. Sakellariou, I., Kefalas, P., Stamatopoulou, I.: Enhancing NetLogo to simulate BDI communicating agents. In: Darzentas, J., Vouros, G.A., Vosinakis, S., Arnellos, A. (eds.) SETN 2008. LNCS (LNAI), vol. 5138, pp. 263–275. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-87881-0_24

    Chapter  Google Scholar 

  16. Sakellariou, I., Kefalas, P., Stamatopoulou, I.: Teaching intelligent agents using NetLogo. In: ACM-IFIP IEEIII, pp. 209–221 (2008)

    Google Scholar 

  17. Sakellariou, I., Kefalas, P., Stamatopoulou, I.: MAS coursework design in NetLogo. In: Proceedings of the International Workshop on the Educational Uses of Multi-Agent Systems (EDUMAS 2009), pp. 47–54 (2009)

    Google Scholar 

  18. Saus, E.R., Johnsen, B.H., Eid, J., Thayer, J.F.: Who benefits from simulator training: personality and heart rate variability in relation to situation awareness during navigation training. Comput. Hum. Behav. 28(4), 1262–1268 (2012)

    Article  Google Scholar 

  19. Schermer, B.W.: Software agents, surveillance, and the right to privacy: a legislative framework for agent-enabled surveillance (2007)

    Google Scholar 

  20. Stanton, N.A., Chambers, P.R., Piggott, J.: Situational awareness and safety. Saf. Sci. 39(3), 189–204 (2001)

    Article  Google Scholar 

  21. Tisue, S., Wilensky, U.: NetLogo: a simple environment for modeling complexity, pp. 16–21, January 2004

    Google Scholar 

  22. Valette, M., Gaudou, B., Longin, D., Taillandier, P.: Modeling a real-case situation of egress using BDI agents with emotions and social skills. In: Miller, T., Oren, N., Sakurai, Y., Noda, I., Savarimuthu, B.T.R., Cao Son, T. (eds.) PRIMA 2018. LNCS (LNAI), vol. 11224, pp. 3–18. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-03098-8_1

    Chapter  Google Scholar 

  23. van Oijen, J., van Doesburg, W., Dignum, F.: Goal-based communication using BDI agents as virtual humans in training: an ontology driven dialogue system. In: Dignum, F. (ed.) AGS 2010. LNCS (LNAI), vol. 6525, pp. 38–52. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-18181-8_3

    Chapter  Google Scholar 

  24. Yau, S.S., Huang, D., Gong, H., Davulcu, H.: Situation-awareness for adaptive coordination in service-based systems. In: 29th Annual International Computer Software and Applications Conference (COMPSAC 2005), vol. 1, pp. 107–112. IEEE (2005)

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science, University of Lahore, Lahore, Pakistan

    Kiran Saleem

  2. Department of Software Engineering, University of Lahore, Lahore, Pakistan

    Hafiz Mahfooz Ul Haque

Authors
  1. Kiran Saleem
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  2. Hafiz Mahfooz Ul Haque
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Correspondence to Hafiz Mahfooz Ul Haque .

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Editors and Affiliations

  1. Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam

    Phan Cong Vinh

  2. The University of the West of England, Bristol, UK

    Abdur Rakib

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Saleem, K., Ul Haque, H.M. (2021). Modelling Situation-Aware Formalism Using BDI Reasoning Agents. In: Vinh, P.C., Rakib, A. (eds) Context-Aware Systems and Applications, and Nature of Computation and Communication. ICCASA ICTCC 2020 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 343. Springer, Cham. https://doi.org/10.1007/978-3-030-67101-3_14

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  • DOI: https://doi.org/10.1007/978-3-030-67101-3_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-67100-6

  • Online ISBN: 978-3-030-67101-3

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