Realtime Agent Navigation With Neural Networks For Computer Games Ross Graham by Ross Graham instant download after payment.

Many 3D graphics applications require the presence of computer-controlled agents that are capable of navigating their way around a virtual 3D world. Computer games are an obvious example of this. One of the greatest challenges in the design of realistic Artificial Intelligence (AI) in computer games is controlling the movement of these agents. Pathfinding strategies are usually employed as the core of any AI movement system. The two main components for basic real-time pathfinding are (i) traveling towards a specified goal and (ii) avoiding dynamic and static obstacles that may litter the path to this goal. Our work focuses on how machine learning techniques, such as Neural Networks and Genetic Algorithms, can be used to enhance an AI agent’s ability to handle pathfinding in real-time by giving them an awareness of the virtual world around them through sensors. This allows the agent to react in real-time to dynamic changes that may occur in the game.