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Mar 26, 2017 01:13 PM IST | Source: PTI

New algorithm can tell when you'll get bored of mobile game

Applied to videogames, the model called survival ensemble can predict what day and at what stage of the game a user will stop playing, and why they will do so.

New algorithm can tell when you'll get bored of mobile game

Scientists have developed a new mathematical model that can predict how soon a user will get bored of a smartphone game, an advance that may help developers create more engaging apps.

Applied to videogames, the model called survival ensemble can predict what day and at what stage of the game a user will stop playing, and why they will do so.

"Already from their first days playing the game, we know with a good degree of certainty what level a user will reach and how many days it will take them," said Africa Perianez, Head of Game Data Science at the video game company Silicon Studio in Japan.

"The main and most pressing priority is to try to extend the player's 'life' and get them to buy as much as possible. Also important is to understand users' needs and design a more entertaining and stimulating game," she said.

The industry has undergone a paradigm shift since the appearance of games for smartphones.

"Companies store a lot of information on users: their actions, connections, purchases, etc. And they are beginning to realise that they need to move towards a data-based development model, which allows them to know who their players are and what they like, and also to predict their reactions," said Perianez.

The Silicon Studio platform adapts automatically to different games and data.

According to the researcher, the system can predict who will leave the game very accurately.

The algorithm uses the so-called 'ensemble' method, "a model that is based on many learning algorithms instead of a single one, thereby improving the prediction accuracy by examining many more correlations and alternative models," Perianez said.

"Every time we run the model, we are actually using 1,000 distinct submodels, each of which focuses on different variables and has different initial conditions," she said.

The team also used a survival analysis algorithm within each submodel.

These models "are used in medical research, for example, to predict when a patient will experience an event of interest, and in biology, to know how particular cells are going to behave in the body," Perianez said.

The researchers have now, for the first time, combined the power of survival algorithms and 'ensemble' models in the field of video games.

"This has enabled us to achieve a high level of prediction accuracy, as the algorithm automatically adapts to the data of the game we want to analyse," said Perianez.
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