Bush Fire Simulation through Emotion-based BDI Methodology

Celine Haren Paschal (1), Muhammad Asyraf bin Khairuddin (2), Cheah Wai Shiang (3), Mohamad Nazri bin Khairuddin Yap (4)
(1) Faculty of Computer Science and IT, UNIMAS, 94300 Kota Samarahan, Sarawak, Malaysia
(2) Faculty of Computer Science and IT, UNIMAS, 94300 Kota Samarahan, Sarawak, Malaysia
(3) Faculty of Computer Science and IT, UNIMAS, 94300 Kota Samarahan, Sarawak, Malaysia
(4) Faculty of Computer Science and IT, UNIMAS, 94300 Kota Samarahan, Sarawak, Malaysia
Fulltext View | Download
How to cite (IJASEIT) :
Haren Paschal, Celine, et al. “Bush Fire Simulation through Emotion-Based BDI Methodology”. International Journal on Advanced Science, Engineering and Information Technology, vol. 13, no. 5, Oct. 2023, pp. 1663-71, doi:10.18517/ijaseit.13.5.18983.
This paper introduces an emotion-based BDI (Belief, desire, intention) methodology to model decision-making during fire evacuation simulations while considering human emotions. The methodology is designed to represent human decision-making processes in graphical representations, which can be simply translated for the implementation phase to simulate various case studies. The methodology utilizes the Belief, Desire, and Intention architecture and the OCEAN Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism) personality behavior to represent decision-making processes graphically, making it easy to translate into a simulation. The methodology aims to create a more realistic simulation closer to real human behavior by incorporating emotions that affect decision-making. In this paper, we validate the emotion-based BDI methodology by replicating the bushfire Australia case study and benchmarking with the previous work on BDI fire evacuation. From the comparison, we found that both results share almost similar patterns. The results show "dead while still unaware" (0% vs. 0%), "dead while deciding what to do" (69% vs. 48%), "dead while defending" (6% vs. 8%), and "dead while preparing to defend" (6% vs 28%), "dead while preparing to escape" (4% vs 0%) and "dead while escaping" (15% vs 20%). The results show that in our Simulation, there is a death related to preparing to escape (4% vs 0%). However, the other causes of death have an almost similar percentage of death causes. Hence, based on the comparison, supporting and validating our emotion-oriented simulation model is considered adequate. Therefore, this emotion-based BDI methodology can systematically reproduce human cognition and emotion.

C. H. Paschal, C. W. Shiang, S. K. Wai, and M. A. Bin Khairuddin, "Developing Fire Evacuation Simulation Through Emotion-based BDI Methodology," Int. J. Informatics Vis., vol. 6, no. 1, pp. 45-52, 2022, doi: 10.30630/joiv.6.1.854.

T. Liu, Z. Liu, M. Ma, T. Chen, C. Liu, and Y. Chai, "3D visual simulation of individual and crowd behavior in earthquake evacuation," Simulation, vol. 95, no. 1, pp. 65-81, 2019, doi: 10.1177/0037549717753294.

E. Argente, E. Del Val, D. Perez-Garcia, and V. Botti, "Normative Emotional Agents: A Viewpoint Paper," IEEE Trans. Affect. Comput., vol. 13, no. 3, pp. 1254-1273, 2022, doi: 10.1109/TAFFC.2020.3028512.

Y. Sí¡nchez-López and E. Cerezo, "Designing emotional BDI agents: Good practices and open questions," Knowl. Eng. Rev., vol. 34, 2019, doi: 10.1017/S0269888919000122.

S. A. Alanazi, M. Shabbir, N. Alshammari, M. Alruwaili, I. Hussain, and F. Ahmad, "Prediction of Emotional Empathy in Intelligent Agents to Facilitate Precise Social Interaction," Appl. Sci., vol. 13, no. 2, 2023, doi: 10.3390/app13021163.

G. Zhao, Y. Li, and Q. Xu, "From Emotion AI to Cognitive AI," Int. J. Netw. Dyn. Intell., pp. 65-72, 2022, doi: 10.53941/ijndi0101006.

Z. Tian, G. Zhang, C. Hu, D. Lu, and H. Liu, "Knowledge and emotion dual-driven method for crowd evacuation," Knowledge-Based Syst., vol. 208, p. 106451, Nov. 2020, doi: 10.1016/j.knosys.2020.106451.

J. Taverner, E. Vivancos, and V. Botti, "Towards a Computational Approach to Emotion Elicitation in Affective Agents," in Proceedings of the 11th International Conference on Agents and Artificial Intelligence, 2019, pp. 275-280. doi: 10.5220/0007579302750280.

J. Gratch and S. Marsella, "A domain-independent framework for modeling emotion," Cogn. Syst. Res., vol. 5, no. 4, pp. 269-306, Dec. 2004, doi: 10.1016/j.cogsys.2004.02.002.

M. Bourgais, P. Taillandier, L. Vercouter, and C. Adam, “Emotion Modeling in Social Simulation: A Survey,” J. Artif. Soc. Soc. Simul., vol. 21, no. 2, 2018, doi: 10.18564/jasss.3681.

M. Shvo, J. Buhmann, and M. Kapadia, "Towards modeling the interplay of personality, motivation, emotion, and mood in social agents," Proc. Int. Jt. Conf. Auton. Agents Multiagent Syst. AAMAS, vol. 4, no. Aamas, pp. 2195-2197, 2019.

L. Luo et al., "Agent-based human behavior modeling for crowd simulation," Comput. Animat. Virtual Worlds, vol. 19, no. 3-4, pp. 271-281, 2008, doi: 10.1002/cav.238.

L. Van Minh, C. Adam, R. Canal, B. Gaudou, H. Tuong Vinh, and P. Taillandier, "Simulation of the Emotion Dynamics in a Group of Agents in an Evacuation Situation," 2012, pp. 604-619. doi: 10.1007/978-3-642-25920-3_44.

H. Jones, J. Saunier, and D. Lourdeaux, "Fuzzy Rules for Events Perception and Emotions in an Agent Architecture," in Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011), 2011. doi: 10.2991/eusflat.2011.34.

M. Kazemifard, A. Zaeri, N. Ghasem-Aghaee, M. A. Nematbakhsh, and F. Mardukhi, "Fuzzy Emotional COCOMO II Software Cost Estimation (FECSCE) using Multi-Agent Systems," Appl. Soft Comput., vol. 11, no. 2, pp. 2260-2270, Mar. 2011, doi: 10.1016/j.asoc.2010.08.006.

W. Zakaria, U. K. Yusof, and S. Naim, "Modelling and simulation of crowd evacuation with cognitive behaviour using fuzzy logic," Int. J. Adv. Soft Comput. its Appl., vol. 11, no. 2, pp. 132-149, 2019.

J. Dias and A. Paiva, "I want to be your friend: Establishing relations with emotionally intelligent agents," 12th Int. Conf. Auton. Agents Multiagent Syst. 2013, AAMAS 2013, vol. 2, pp. 777-784, 2013.

G. Marreiros, R. Santos, C. Ramos, and J. Neves, "Context-Aware Emotion-Based Model for Group Decision Making," IEEE Intell. Syst., vol. 25, no. 2, pp. 31-39, Mar. 2010, doi: 10.1109/MIS.2010.46.

M. El Jed, N. Pallamin, J. Dugdale, and B. Pavard, "Modelling character emotion in an interactive virtual environment," AISB 2004 Conv. Symp. Lang. Speech Gesture Expressive Characters, 2004.

M. Ochs, N. Sabouret, and V. Corruble, "Simulation of the Dynamics of Nonplayer Characters' Emotions and Social Relations in Games," IEEE Trans. Comput. Intell. AI Games, vol. 1, no. 4, pp. 281-297, Dec. 2009, doi: 10.1109/TCIAIG.2009.2036247.

N. Pelechano, K. O'Brien, B. Silverman, and N. Badler, "Crowd Simulation Incorporating Agent Psychological Models, Roles and Communication," Jan. 2005. doi: 10.21236/ADA522128.

B. G. Silverman, M. Johns, J. Cornwell, and K. O'Brien, "Human Behavior Models for Agents in Simulators and Games: Part I: Enabling Science with PMFserv," Presence Teleoperators Virtual Environ., vol. 15, no. 2, pp. 139-162, Apr. 2006, doi: 10.1162/pres.2006.15.2.139.

A. Zoumpoulaki, N. Avradinis, and S. Vosinakis, "A Multi-agent Simulation Framework for Emergency Evacuations Incorporating Personality and Emotions," 2010, pp. 423-428. doi: 10.1007/978-3-642-12842-4_54.

M. Ten, W. Cheah, and Y. W. Sim, "Engineering Blockchain Enabling Win A Fortune Game among Novice through eAOM," in 14th ACM Web Science Conference 2022, Jun. 2022, pp. 443-450. doi: 10.1145/3501247.3539018.

N. Hussain, C. W. Shiang, S. Loke, and M. A. bin Khairuddin, "A Multi-Agent Simulation Evacuation Model Using The Social Force Model: A Large Room Simulation Study," JOIV Int. J. Informatics Vis., vol. 6, no. 1-2, p. 221, May 2022, doi: 10.30630/joiv.6.1-2.929.

N. Hussain and C. W. Shiang, "Modelling of Crowd Evacuation with Communication Strategy Using Social Force Model," J. Optim. Ind. Eng., vol. 15, no. 1, pp. 233-241, 2022, doi: 10.22094/JOIE.2021.1941247.1898.

S. F. binti Zulkifli, C. Waishiang, M. A. bin Khairuddin, N. binti Jali, and Y. R. binti Bujang, “How to Model an Engaging Online Quiz? The Emotion Modeling Approach," J. Telecommunictions Inf. Technol., vol. 1, no. 2022, pp. 54-63, Mar. 2022, doi: 10.26636/jtit.2022.156221.

N. YenChern, C. WaiShiang, S. KengWai, M. A. bin Khairuddin, N. bt Jali, and E. ak Mit, "Developing fire evacuation simulation through BDI-based modelling and simulation," J. Phys. Conf. Ser., vol. 2107, no. 1, p. 012047, Nov. 2021, doi: 10.1088/1742-6596/2107/1/012047.

S. K. Wai, C. WaiShiang, M. A. Bin Khairuddin, Y. R. B. Bujang, R. Hidayat, and C. H. Paschal, "Autonomous Agents in 3D Crowd Simulation Through BDI Architecture," JOIV Int. J. Informatics Vis., vol. 5, no. 1, p. 1, Mar. 2021, doi: 10.30630/joiv.5.1.371.

C. Adam and B. Gaudou, "Modelling Human Behaviours in Disasters from Interviews: Application to Melbourne Bushfires," J. Artif. Soc. Soc. Simul., vol. 20, no. 3, 2017, doi: 10.18564/jasss.3395.

S. T. Tzeng, N. Ajmeri, and M. P. Singh, "Noe: Norm Emergence and Robustness Based on Emotions in Multiagent Systems," Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 13239 LNAI, pp. 62-77, 2022, doi: 10.1007/978-3-031-16617-4_5.

S. T. Tzeng, "Engineering Normative and Cognitive Agents with Emotions and Values," Proc. Int. Jt. Conf. Auton. Agents Multiagent Syst. AAMAS, vol. 3, pp. 1878-1880, 2022.

J. Luo, M. Dastani, T. Studer, and B. Liao, "What Do You Care About: Inferring Values from Emotions," 22nd Int. Conf. Auton. Agents Multiagent Syst. (AAMAS 2023), pp. 2289-2291, 2023.

G. Šimić et al., "Understanding Emotions: Origins and Roles of the Amygdala," Biomolecules, vol. 11, no. 6, p. 823, May 2021, doi: 10.3390/biom11060823.

K. Taveter and T. Iqbal, "Theory of Constructed Emotion Meets RE," in 2021 IEEE 29th International Requirements Engineering Conference Workshops (REW), Sep. 2021, pp. 383-386. doi: 10.1109/REW53955.2021.00067.

T. Iqbal, J. G. Marshall, K. Taveter, and A. Schmidt, "Theory of constructed emotion meets RE: An industrial case study," J. Syst. Softw., vol. 197, p. 111544, Mar. 2023, doi: 10.1016/j.jss.2022.111544.

R. Pekrun et al., "A three-dimensional taxonomy of achievement emotions.," J. Pers. Soc. Psychol., vol. 124, no. 1, pp. 145-178, Jan. 2023, doi: 10.1037/pspp0000448.

S. Mascarenhas, M. Guimarí£es, P. A. Santos, J. Dias, R. Prada, and A. Paiva, "FAtiMA Toolkit -- Toward an effective and accessible tool for the development of intelligent virtual agents and social robots," 2021, [Online]. Available: http://arxiv.org/abs/2103.03020

M.-T. Ho, N.-T. B. Le, P. Mantello, M.-T. Ho, and N. Ghotbi, "Understanding the acceptance of emotional artificial intelligence in Japanese healthcare system: A cross-sectional survey of clinic visitors' attitude," Technol. Soc., vol. 72, p. 102166, Feb. 2023, doi: 10.1016/j.techsoc.2022.102166.

Y. Sullivan, S. Nyawa, and S. F. Wamba, "Combating Loneliness with Artificial Intelligence: An AI-Based Emotional Support Model," Proc. Annu. Hawaii Int. Conf. Syst. Sci., vol. 2023-Janua, pp. 4443-4452, 2023.

M. Gutica and S. Petrina, "Emotional Agents in Educational Game Design," in Research Anthology on Game Design, Development, Usage, and Social Impact, IGI Global, 2022, pp. 411-432. doi: 10.4018/978-1-6684-7589-8.ch021.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
    2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
    3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).