Artificial Intelligence (AI) Prediction of Atari Game Strategy by using Reinforcement Learning Algorithms

Video games produce reactionary, resilient, or clever behavior, mostly on non-player characters (NPCs), who resemble Artificial Intelligence (AI). Since the launch of video games in the 1950s AI has become an important component. AI is a separate subfield in computer games that varies from AI. Instead of learning the machine or determining it is used to enhance the player experience. The concept of an AI opponent was popularized during the golden age of arcade videogames in the form of graded levels of difficulty, distinct action styles and events based on the player’s involvement. Modern games also apply current strategies such as path-finding and decision-making bodies to control NPCs’ actions. AI is used often in mechanisms, such as data mining and process content creation, which is not immediately accessible to the user. We were creating an AI Organization to use the same hyper parameter to learn how to play a variety of Atari games. Over time it became a more theory-oriented project, in which we discussed numerous ways to use our methods for deep learning, and Put them on a game, Pong, rather than a game package.