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Our "soft clustering" strategy that allows gamers to move between clusters accommodates two types of potential variability exhibited by players
in Battlefield 3. First, certain players might have a play type that is a real hybrid between two (or extra) frequent play types
shared by many gamers. That is relevant both from the designers and builders point of view that
benefit from an architecture that is simpler to keep up and reuse, but also from the point of view of the more refined interactions
with the sport-world that NPCs can obtain. Network Architecture and Training.
However, contemplating the non-trivial dimension of the sport
space, such a reward function would have required an extended training time.
To stabilize coaching, we normalize the reward and enhance the
dimensions of the discriminator coaching dataset.
These results appear in keeping with the fact that the Atari-HEAD dataset ought to have less latency between the
states and actions because of its different knowledge assortment setup.