## 1 Introduction  
Individuals are in danger when an emergency occurs in an environment that is not suited for making sound judgments during an evacuation. People may react unpredictably to panic and chaos, prioritizing immediate safety and moving to what they perceive as a safe location. However, this is not always the best way to exit an emergency situation. Measures must be developed to guide individuals to evacuate in a timely and effective manner to ensure safety [1]. Although the mining industry has made significant strides in enhancing safety, it remains one of the most hazardous industries worldwide [2]. Therefore, it is imperative that the industry adopt additional measures to prevent or alleviate hazards [3]. However, the health and safety of miners have improved significantly over time. According to the latest data from NIOSH depicted in Figure 1, there has been a decline in both fatality and injury rates, despite a persistent rise in production [4]. Nevertheless, further enhancements and initiatives are essential to achieve and maintain a \"zero incident\" operation [5]. The mining industry has implemented several safety measures to improve the evacuation process during emergencies. Although traditional methods have been replaced by more advanced technologies to reduce the risk of accidents and enhance evacuation times, the success of an evacuation depends not only on technology but also on miners' behavior, social interactions, and the speed of information transmission during an emergency. Although optimizing evacuation routes plays a crucial role in emergencies, modeling evacuation behavior and individual movement is a challenging endeavor. Psychological, social, and environmental factors influence people's decision-making in emergencies. There are two significant research challenges in the evacuation process and analysis: (1) integrating the effect of individuals' adaptive behavior and (2) simulating complex evacuation scenarios that involve large crowds at the individual level, given the high complexity of the process [6]. Operational research often employs simulation models to represent real-world systems and evaluate scenarios across a range of behaviors. This is often accomplished using discrete event simulation (DES) and agent-based simulation (ABS) [7]. DES is normally used for simulating large-scale evacuations from hazardous situations, while ABS is favored for examining individual behaviors during evacuation scenarios. Models that incorporate adaptation and learning mechanisms are particularly valuable for the development and evaluation of evacuation strategies. ABS is a versatile tool applicable across various contemporary life domains, including biological and social systems, as well as physical systems that involve humans. For example, ABS can simulate extinct societies or establish markets for yet-to-be-introduced products and services [8]. The suitability of ABS for simulating human behavior lies in its ability to characterize interactions between individuals, the impact of these interactions on individual perceptions and desires, and the inherent uncertainty of such processes at an individual level rather than at a population level. ABS also enables the formal depiction of social interactions among individuals with diverse attributes, while facilitating the examination of social network configurations [9]. The use of simulation techniques for evacuation purposes has widely been adopted in different industries. [PERSON] et al. [10] developed an agent-based discrete event simulation for transportation evacuation based on a hybrid continuous and cell space. [PERSON] et al. [11] employed distributed building evacuation simulators to simulate a system representing the individual, intelligent, and interacting agents that cooperate and compete while evacuating the building. [PERSON] et al. [12] proposed a dynamic evacuation simulation structure for a hazardous gas diffusion scheme by integrating dynamic analysis models into the geographical information system (GIS).