# New Game Artificial Intelligence Tools for Virtual Mine on Unreal Engine
## 1 Introduction  
The concept of gamification of virtual reality tools for miners training, ensuring the safety of workers, and designing mining operations was launched in the early 2000s. Initially, gamification was understood as a direction for the development of simulation systems for training personnel, assessing their competencies, developing knowledge management, and implementing best practices [1]. The first attempts to build virtual 3D models of mines with an interface similar to computer games were not aimed at creating a fully interactive digital reality but rather animation software controlled by mouse and keyboard [2]. Subsequently, since the beginning of the 2010s, virtual reality tools such as VR glasses and hand-held manipulators, volumetric motion sensors, and powerful computing systems have started to be used [3]. Here an and below the terminology used in this article is explained in Appendix A. To date, virtual reality game models in the mining sector incorporate the advanced achievements of Industry 4.0 (artificial intelligence, digital 3D models, and smart sensors) and are part of the Mining 4.0 technology platform [2]. Mining engineers training using virtual reality is gaining importance [4]. This process not only improves the quality of training of mining experts but also significantly reduces the number of possible emergency and pre-emergency situations, taking into account the experience gained and practical training for the application of proactive measures in underground space as close as possible to real scenarios [2; 3; 4]. In particular, virtual gaming systems are widely used to conduct introductory briefings and tours of underground workings, prepare firefighting activities, and eliminate the consequences of accidents underground, which makes it possible to reduce occupational injuries by 1.5-2.5 times [5]. They also improve the design and management of disturbed land reclamation through high-level personnel training [6]. The use of gaming virtual simulator systems in mines is associated with the difficulty of recreating the real situation since geotechnics and technologies are developing quite rapidly. Nevertheless, virtual gaming technologies allow, at minimal cost, the automatic launch of risk management and competency adjustment procedures [7]. The analysis of literary sources showed the high contribution of scientists and practitioners in the development of computer applications, the use of virtual and augmented reality technologies, as well as artificial intelligence objects [8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18]. These works have covered many diverse scientific and technical fields, from the development of object detection systems [19], education [20; 21], cinematography [22], equipping scientific laboratories [23], solving tourism problems [24], modeling and optimization [25], to gaming applications [26; 27; 28]. However, not one work presented the process of expanding the possibilities of developing game artificial intelligence. This is precisely the main goal disclosed in the presented article. Artificial intelligence in video games is a system that determines the believable behavior of in-game characters controlled by a computer. The presence of a believable game AI is one of the necessary conditions for the player's quality immersion in the virtual world. Game AI is rarely associated with any kind of deep intelligence but rather with the illusion of intelligence. Game AI developers often try to create believable human behavior, but the actual intelligence that can be programmed is quite limited and painfully fragile. Expectation plays a huge role in how people perceive the world, and if expectations are not properly managed, then even truly intelligent behavior on a human level can be perceived as incompetent and clearly inhuman. Game AI should focus on one thing and one thing only: enabling developers to create an engaging experience for the player. Every technique used, every trick played, and every algorithm coded must support this single goal.