Abstract: The Gamer's Personal Network (GPN) is a consumer/server expertise created by WTFast for making the network efficiency of online video games faster and more dependable. GPN s use center-mile servers and proprietary algorithms to better join on-line video-game players to their game's servers throughout a large-area community. MINECRAFT JAVA are a large entertainment market and network latency is a key side of a participant's aggressive edge. This market means many various approaches to network architecture are applied by completely different competing companies and that these architectures are always evolving. Ensuring the optimum connection between a client of WTFast and the online recreation they want to play is thus an extremely difficult drawback to automate. Using machine learning, we analyzed historical network data from GPN connections to explore the feasibility of network latency prediction which is a key part of optimization. Our subsequent step will probably be to collect dwell data (including client/server load, packet and port information and particular sport state info) from GPN Minecraft servers and bots. We'll use this information in a Reinforcement Studying mannequin along with predictions about latency to alter the purchasers' and servers' configurations for optimum network performance. These investigations and experiments will improve the quality of service and reliability of GPN systems.