# A Study on Design Requirement Development and Satisfaction for Future Virtual World Systems
## 2 Trend Analysis
### Intelligence  
Game intelligence (i.e., computational intelligence in games) applies a set of computational approaches to address complex problems in games [39]. Many AI techniques have been widely applied in game worlds (called game AI) for creating a sense of challenging, enriching human-computer interaction, providing better content and bringing additional experience to users [40]. A previous study (found in the Supplementary Materials) has rendered the milestones of game AI innovation in nonplayer character (NPC) behavior, procedural content generation (PCG), and narrativity. The study shows that game AI in NPC can endow NPCs with believable or human-like characteristics in interaction. The game AI in PCG can automatically generate a complex world system, many 3D models, and a full scenario with random quests. It also shows that game AI can even develop game plots from interactive storytelling to augment users' dynamic and immersive gaming experience. To further improve game AI, machine learning techniques (e.g., reinforcement learning) have been applied to games, in addition to planning and tree search. They have become either the dominant or the secondary method in NPC behavior learning, player modeling, PCG, computational narrative, believable agents, AI-assisted game design, and general game AI [40]. [PERSON] et al. [41] surveyed the cutting-edge machine learning approaches applied in PCG. Some artificial intelligence techniques have been applied in story generation [42], such as genetic algorithms.  
Outside of games, AI can simulate virtual human, virtual nonhuman, crowds, and other representations in virtual environments for scientific simulation or other nongaming purposes [43]. Human-level AI agents are important ingredients in social virtual worlds with autonomous functions  
Figure 5: Trends of the immersive technology and market: (**a**) immersive device shipments worldwide from 2015 to 2023, by product type; (**b**) immersive technology consumer market revenue worldwide from 2018 to 2021; (**c**) a number of new virtual reality sensory device releases along with years, by category, where all the figures before 2000 are aggregated to 2000; (**d**) value of the haptic technology market in the Asia-Pacific region from 2016 to 2017.  
(e.g., navigation guidance) [44]. An artificial life environment can be created through individual or group learning to generate virtual creatures (e.g., dolphins) with autonomous behaviors to gain more knowledge on nature life [45]. Crowd agents in an immersive environment can be applied to simulate emergency responsiveness [46]. Realistic virtual terrains can be generated with conditional generative adversarial networks [47], which can facilitate virtual world authoring with low cost. Moreover. AI has also been used for human-machine interaction, such as voice control in mixed reality [48]. Through natural language processing, a new environment for speaking and listening skill improvement can be created [49]. The above trends show that we can witness the increasing adoption and improvement of intelligent techniques in virtual worlds.