Crowd simulation is the process of simulating the movement (or ) of a large number of entities or characters. It is commonly used to create virtual scenes for visual media like films and video games, and is also used in crisis training, architecture and urban planning, and evacuation simulation. Crowd simulation may focus on aspects that target different applications. For realistic and fast rendering of a crowd for visual media or virtual cinematography, reduction of the complexity of the 3D scene and image-based rendering are used, while variations (changes) in appearance help present a realistic population. In games and applications intended to replicate real-life human crowd movement, like in evacuation simulations, simulated agents may need to navigate towards a goal, avoid collisions, and exhibit other human-like behavior. Many crowd steering algorithms have been developed to lead simulated crowds to their goals realistically. Some more general systems are researched that can support different kinds of agents (like cars and pedestrians), different levels of abstraction (like individual and continuum), agents interacting with smart objects, and more complex physical and social dynamics. History There has always been a deep-seated interest in the understanding and gaining control of motional and behavior of crowds of people. Many major advancements have taken place since the beginnings of research within the realm of crowd simulation. Evidently many new findings are continually made and published following these which enhance the scalability, flexibility, applicability, and realism of simulations: In 1987, behavioral animation was introduced and developed by Craig Reynolds. He had simulated flocks of birds alongside schools of fish for the purpose of studying group intuition and movement. All agents within these simulations were given direct access to the respective positions and velocities of their surrounding agents. The theorization and study set forth by Reynolds was improved and built upon in 1994 by Xiaoyuan Tu, Demetri Terzopoulos and Radek Grzeszczuk. The realistic quality of simulation was engaged with as the individual agents were equipped with synthetic vision and a general view of the environment within which they resided, allowing for a perceptual awareness within their dynamic habitats. Initial research in the field of crowd simulation began in 1997 with Daniel Thalmann's supervision of Soraia Raupp Musse's PhD thesis. They present a new model of crowd behavior in order to create a simulation of generic populations. Here a relation is drawn between the autonomous behavior of the individual within the