Autonomous Agents in 3D Crowd Simulation Through BDI Architecture

Wai, Sim Keng; Cheah, Whye Lian; Khairuddin, Muhammad Asyraf bin; Bujang, Yanti Rosmunie; Hidayat, Rahmat; Paschal, Celine Haren

doi:10.30630/joiv.5.1.371

Cited by 8 publications

(11 citation statements)

References 19 publications

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“…Our methodology is to promote Agentoriented modeling for modeling a complex socio-technical system [24]- [28]. As stated in [29], the Simulation consists of a residential area surrounded by a forest with 100 houses. One occupant stays in each house.…”

Section: Methodsmentioning

confidence: 99%

Bush Fire Simulation through Emotion-based BDI Methodology

Haren Paschal,

Bin Khairuddin,

Wai Shiang

et al. 2023

Int. J. Adv. Sci. Eng. Inf. Technol.

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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.

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Section: Methodsmentioning

confidence: 99%

Bush Fire Simulation through Emotion-based BDI Methodology

Haren Paschal,

Bin Khairuddin,

Wai Shiang

et al. 2023

Int. J. Adv. Sci. Eng. Inf. Technol.

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“…Simulations that exploit Unity as the engine and visualization tool and the BDI model as a reference for implementing individual agents have been developed in a few domains, including large urban areas [59], fire evacuation [60], first aid emergency [61], gas and oil industry [62], and bushfires in Australia [63]. Those works are driven by an application to simulate and lack re-usability in other contexts.…”

Section: Related Work Virtual Reality and Multiagent Systems (Mas)mentioning

confidence: 99%

VEsNA, a Framework for Virtual Environments via Natural Language Agents and Its Application to Factory Automation

Gatti

Mascardi

2023

Robotics

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Automating a factory where robots are involved is neither trivial nor cheap. Engineering the factory automation process in such a way that return of interest is maximized and risk for workers and equipment is minimized is hence, of paramount importance. Simulation can be a game changer in this scenario but requires advanced programming skills that domain experts and industrial designers might not have. In this paper, we present the preliminary design and implementation of a general-purpose framework for creating and exploiting Virtual Environments via Natural language Agents (VEsNA). VEsNA takes advantage of agent-based technologies and natural language processing to enhance the design of virtual environments. The natural language input provided to VEsNA is understood by a chatbot and passed to an intelligent cognitive agent that implements the logic behind displacing objects in the virtual environment. In the complete VEsNA vision, for which this paper provides the building blocks, the intelligent agent will be able to reason on this displacement and on its compliance with legal and normative constraints. It will also be able to implement what-if analysis and case-based reasoning. Objects populating the virtual environment will include active objects and will populate a dynamic simulation whose outcomes will be interpreted by the cognitive agent; further autonomous agents, representing workers in the factory, will be added to make the virtual environment even more realistic; explanations and suggestions will be passed back to the user by the chatbot.

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“…The agent models are transformed into a BDI based simulation Unity platform. The emotion-based BDI methodology can be transformed into the emotion-based BDI simulation by adopting our previous work [18]. A BDI plugin tool has been created 18] using the programming language provided by Unity3D to develop the BDI simulation model.…”

Section: F Step 6 Platform Specific Design and Modellingmentioning

confidence: 99%

“…Hence, to develop the emotion-based fire evacuation simulation through emotion-based BDI methodology, the same Unity3D tools will be used to implement the proposed methodology. For example, based on previous work in [18] Table 6 shows the mapping of the scenario model into Unity3D construct. From the modeling of the behavior model, we can transform design models into an emotion-based BDI simulation platform, as reported in this section.…”

Section: F Step 6 Platform Specific Design and Modellingmentioning

confidence: 99%

Developing Fire Evacuation Simulation Through Emotion-based BDI Methodology

Paschal

Shiang

Wai

et al. 2022

JOIV : Int. J. Inform. Visualization

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Fire evacuation simulation is a tool to study human behavior in dealing with fire. It has been used for safety policy management studies, building safety analysis, and human safety understanding. To date, modeling the fire evacuation behavior is paying much attention in which works have been done to design and develop building model, fire model, human decision model, and human emotion decision model. As fire evacuation simulation is important, the BDI methodology is introduced by authors to ease modeling and simulation of human behavior in a fire evacuation. Continue the success of capturing and modeling the human behavior in a fire evacuation. This paper presents the influence of human emotion in fire evacuation simulation. In this paper, the emotion-based BDI methodology is presented with a walkthrough example of how emotion can influence the human decision in a fire spreading scenario. The OCEAN model of personality is used to handle the emotional properties in the methodology. Different people have different types of personalities, which can affect both decision-making and emotion in different situations. A fire evacuation simulation is developed by using the Unity3D game engine. The simulation is created based on the emotion-based BDI methodology presented. Hence, the emotion-based BDI methodology can be used to model human behavior and emotional states in a fire evacuation. Overall, the paper introduces a new insight into how to model human behavior in fire evacuation decision-making systematically.

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Autonomous Agents in 3D Crowd Simulation Through BDI Architecture

Cited by 8 publications

References 19 publications

Bush Fire Simulation through Emotion-based BDI Methodology

Bush Fire Simulation through Emotion-based BDI Methodology

VEsNA, a Framework for Virtual Environments via Natural Language Agents and Its Application to Factory Automation

Developing Fire Evacuation Simulation Through Emotion-based BDI Methodology

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