GDC Presentation - March 24, 2022
On modern mobile devices, there are a number of systems which aim to improve the game experience, delivering high and stable frame rates while keeping the device at manageable temperatures.
Often the standard method of tuning these device systems is through either lab based testing, which is not scalable, or alternatively, using real world analysis. However systems on device don't run in isolation and when tuning parameters, other factors can be at play which potentially obfuscate the impact of the change.
By leveraging domain knowledge and building an explicit causal model of the system, a better indication of the treatment effect size can be measured as well as other useful insights on the performance of such systems.
Learn about how causal modeling using bayesian networks can be used to better evaluate any changes made, based on real world cases carried out to improve game performance on mobile devices.
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