Patrolling AI Systems in Video Games

Abstract

Artificial Intelligence is a common element in digital video games and it is one of the most essential component in modern games. Modern games are populated with Non-Player Characters (AI Characters) that performs different activities. Realism is dominating in games and AI behavio rs are expected to be more realistic in games. Games that has poor unrealistic AI elements are facing heavy criticism from the player bases. Further, modern games are highly dynamic. Classical games had static environment with less or no changes in it. Such environments made implementation of AI easy and simple. In modern games, Progressive terrain generation and other such content generation methods increases the complexities of building an efficient AI for games that has many changes in real time. One of the most common AI in games is Patrolling AI especially in Shooter and Adventure Games. Patroling AI involves path finding and obstacle attack or defense. RRT algorithm and its variants are highly successful Probabilistic Determination AI that produced effective results in real time robotic movement. In order to build efficient Patrolling AI for games, a real time RRT* variant called RT-RRT* algorithm was employed. The algorithm is flexible enough to add various behaviors in addition to path finding which makes it more suitable for games. The algorithm takes samples from the environment and construct the efficient path. Also the algorithm inspect the environment in run time to ensure that no moving obstacle blocks the path. In such case, it rewires and create a new path. In order to manage the dynamic obstacles, a Real Time Obstacle Handling Algorithm was designed and employed in a dynamic game environment. The algorithms inputs the obstacles types and parameters. On identifying the obstacle approaching the AI in terrain, it tells the agent to perform the needed actions. The simulations was carried out using Unity Game Engine. The model proposed helped to create efficient patrolling AI that handle two major aspects of patrolling which is Path finding and Obstacle handling. The model will be highly suitable for dynamic game environments with lots of uncertainty and emergence.