Would be interesting to get your hands on a large set of replays from a lot of gosu players and run some machine learning offline prior to each map for the current match map. Would be fun to experiment with the data and see if it would be possible to infer game tactics from professional players and "simulate" those against another bot based on the current game state.
> Would be interesting to get your hands on a large set of replays from a lot of gosu players and run some machine learning offline prior to each map for the current match map. There are probably too many variables in Starcraft for this to be practical. With a game like chess there's a fairly obvious set of state variables to keep track of (max of 32 pieces that each have a position in essentially an 8x8 2D array), w…
That's why it would be interesting to see how much can be inferred from offline learning first.
For example, looking at unit positions over time for the map can be quite rewarding, especially between the different phases of the game (early, mid, late).