You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I'm assuming that when training the AI, it had only 4 outputs (north,south,east,west). Apologies if that's a faulty assumption.
For training the network, you might consider training it for a few additional outputs - not because you need them to play the game, but because by needing to provide them, the network will need an additional awareness of the game mechanics.
4 outputs (N/S/E/W) for when a move in that direction is possible, 0 if not possible.
4 outputs (N/S/E/W) for when a move in that direction will merge tiles.
1 output for a complexity score of the remaining tiles, after whatever mergers happen for the requested move.
The 'human' analog of training for these outputs would be 'learning the rules of the game' - It'll know when tiles merge and it'll know when moves are invalid, and it may internalize some of the logic for that in its decision process for moves.
The text was updated successfully, but these errors were encountered:
I'm assuming that when training the AI, it had only 4 outputs
(north,south,east,west). Apologies if that's a faulty assumption.
For training the network, you might consider training it for a few
additional outputs - not because you need them to play the game, but
because by needing to provide them, the network will need an additional
awareness of the game mechanics.
4 outputs (N/S/E/W) for when a move in that direction is possible, 0 if
not possible.
4 outputs (N/S/E/W) for when a move in that direction will merge tiles.
1 output for a complexity score of the remaining tiles, after whatever
mergers happen for the requested move.
The 'human' analog of training for these outputs would be 'learning the
rules of the game' - It'll know when tiles merge and it'll know when moves
are invalid, and it may internalize some of the logic for that in its
decision process for moves.
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
<#8?email_source=notifications&email_token=AAH4CSV5W7G5J2JVCT5WPR3PXSTULA5CNFSM4HP7QS52YY3PNVWWK3TUL52HS4DFUVEXG43VMWVGG33NNVSW45C7NFSM4GWD7XFQ>,
or mute the thread
<https://github.com/notifications/unsubscribe-auth/AAH4CSVAQXZBUN5YM577LVLPXSTULANCNFSM4HP7QS5Q>
.
I'm assuming that when training the AI, it had only 4 outputs (north,south,east,west). Apologies if that's a faulty assumption.
For training the network, you might consider training it for a few additional outputs - not because you need them to play the game, but because by needing to provide them, the network will need an additional awareness of the game mechanics.
4 outputs (N/S/E/W) for when a move in that direction is possible, 0 if not possible.
4 outputs (N/S/E/W) for when a move in that direction will merge tiles.
1 output for a complexity score of the remaining tiles, after whatever mergers happen for the requested move.
The 'human' analog of training for these outputs would be 'learning the rules of the game' - It'll know when tiles merge and it'll know when moves are invalid, and it may internalize some of the logic for that in its decision process for moves.
The text was updated successfully, but these errors were encountered: