Factors affecting gaming engines: Analytical Study

Abstract

The apparent evolution of machine learning in gaming is the application of machine learning techniques. One major use can be the creation of much more realistic, smarter and responsive characters in the games those which can learn new abilities from the various actions of the players and then use these actions to counter-perform the tactics and the strategies as well as also produce many unscripted responses when these actions are being observed by the in-game player actions. The methodology of analytics is providing a better understanding of the gaming industry data and how it is going to affect a lot of businesses in the future. Also, monetization models in gaming have been steadily shifting to lower outspoken pricing all the way down to free-to-play balanced with increased in-game purchases and microtransactions which give profit over time. still, this model of course requires both long-term player engagement and desirable in-game purchases. Machine learning can help in the design of these products and in deciding when and how to present them to the player.