Celine Haren Paschal, Muhammad Asyraf Bin Khairuddin, Cheah Wai Shiang, Mohamad Nazri bin Khairuddin Yap
{"title":"Bush Fire Simulation through Emotion-based BDI Methodology","authors":"Celine Haren Paschal, Muhammad Asyraf Bin Khairuddin, Cheah Wai Shiang, Mohamad Nazri bin Khairuddin Yap","doi":"10.18517/ijaseit.13.5.18983","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":14471,"journal":{"name":"International Journal on Advanced Science, Engineering and Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal on Advanced Science, Engineering and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18517/ijaseit.13.5.18983","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
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.
本文介绍了一种基于情感的BDI(信念、欲望、意图)方法,在考虑人类情感的情况下对火灾疏散模拟中的决策进行建模。该方法旨在以图形表示人类决策过程,可以简单地转换为实现阶段,以模拟各种案例研究。该方法利用信念、欲望和意图架构和OCEAN(开放性、严谨性、外向性、宜人性和神经质)人格行为来图形化地表示决策过程,使其易于转化为模拟。该方法旨在通过纳入影响决策的情绪,创造一个更接近真实人类行为的逼真模拟。在本文中,我们通过复制澳大利亚森林大火的案例研究,并与之前关于BDI火灾疏散的工作进行基准测试,验证了基于情感的BDI方法。通过比较,我们发现两种结果有着几乎相似的模式。调查结果显示,“不知情时死亡”(0%对0%)、“决定怎么做时死亡”(69%对48%)、“防御时死亡”(6%对8%)、“准备防御时死亡”(6%对28%)、“准备逃跑时死亡”(4%对0%)和“逃跑时死亡”(15%对20%)。结果表明,在我们的模拟中,存在与准备逃跑相关的死亡(4% vs 0%)。然而,其他死因占死亡原因的比例几乎相同。因此,基于比较,支持和验证我们的情感导向模拟模型是足够的。因此,这种基于情感的BDI方法可以系统地再现人类的认知和情感。
期刊介绍:
International Journal on Advanced Science, Engineering and Information Technology (IJASEIT) is an international peer-reviewed journal dedicated to interchange for the results of high quality research in all aspect of science, engineering and information technology. The journal publishes state-of-art papers in fundamental theory, experiments and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion and concise conclusion. As our commitment to the advancement of science and technology, the IJASEIT follows the open access policy that allows the published articles freely available online without any subscription. The journal scopes include (but not limited to) the followings: -Science: Bioscience & Biotechnology. Chemistry & Food Technology, Environmental, Health Science, Mathematics & Statistics, Applied Physics -Engineering: Architecture, Chemical & Process, Civil & structural, Electrical, Electronic & Systems, Geological & Mining Engineering, Mechanical & Materials -Information Science & Technology: Artificial Intelligence, Computer Science, E-Learning & Multimedia, Information System, Internet & Mobile Computing