In the game industry, software projects extend over several years: for instance, a typical AAA game is developed for 3 to 5 years. To make the development process easier for the developers, tools are put at their disposal to help with, for instance, the artistic creation process or code integration.
The project aims at developing a new type of Reinforcement Learning algorithm that would allow to retain more control over the artificial agent once its training is completed. This framework would combine modern unsupervised modeling techniques to capture the variability of a set of demonstrations and user-defined programmatic functions that can characterise particularly important factors of variations. Ultimately, the user would be able to specify to the learned agent what type of behavior should be executed at test-time.
With techniques such as Motion Matching and large motion capture data sets, video game characters have become very realistic for user-controlled motion. The next stage towards realistic video game characters is to incorporate physical interaction into the characters behaviour so that it reacts to new environments in a realistic way.