Reinforcement Learning terminology :-) In Go the state is the board situation (stones, player to move, ko info, etc.), the action is simply the move. Together they form state-action pairs.
A standard transposition table typically only has state values; action values can then be inferred from a one ply search. In a full graph representation the state-action values are the values of the edges. Erik On Mon, Oct 27, 2008 at 4:03 PM, Mark Boon <[EMAIL PROTECTED]> wrote: > > On 27-okt-08, at 12:45, Erik van der Werf wrote: > > Using state-action values > > appears to solve the problem. > > What are 'state-action values'? > Mark > > _______________________________________________ > computer-go mailing list > computer-go@computer-go.org > http://www.computer-go.org/mailman/listinfo/computer-go/ > _______________________________________________ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/
