Unity Helsinki Using Reinforcement Learning for Optimizing the Player Lifecycle

Welcome to our second online lunch MeetUp! 💪

We will start our agenda at 11:30 and have two 25-minute long sessions on machine learning at Unity GameTune team!

Here in our Helsinki office, GameTune team is building a machine learning tool for game developers. With GameTune, studios can adjust the game in real-time to deliver the optimal experience to players.

Recently, GameTune has started to utilize reinforcement learning in production. This allows the product to optimize the full player lifecycle and to solve more complex use cases – like level-balancing and interstitial ad frequency optimization – that maximize the lifetime value (LTV) of players. GameTune has now a fully automated solution to optimize sequential decisions per user by using reinforcement learning.

Come and hear us talk about optimizing player lifecycle with machine learning!

🍔 Our lunch agenda will be the following 🍔

11:30-11:40 Check in and Life at Unity by Austin Sears
11:40-12:05 Jenny Hissa on building GameTune product at Unity in Helsinki
12:05-12:30 Markus Ojala on using reinforcement learning for optimizing the player lifecycle
12:30-13:00 Q&A

Join the event to learn how and why to change your supervised machine learning to reinforcement learning

Read more about GameTune: https://unity.com/products/gametune