How do you handle n_i = 0 in equation 1.2? I'd assume that if a heuristic says a move is really bad (H_B = 0), then you'd want to avoid simulations for a while.
Also, has mango experimented with other related strategies for a soft transition? In my own mathematical recreation, I came up with a slightly variant method. Just to keep the text short, here's the notation that I'll use... N = number of simulations through parent node n_i = number of simulations through this node w_i = winning simulations through this node v_i = w_i / n_i H_B = heuristic_bias n_h = heuristic confidence (used in my equation) UCTdelta = sqrt(ln(N)/n_i) p_hat = estimated probability of winning with soft transition ... then equation 1.2 is p_hat + UCTdelta For you, p_hat = (w_i + H_B)/n_i I derived and posted the following formula to the list: p_hat = (w_i + n_h*H_B)/(n_i+n_h) The two equations are fairly similar... especially if n_h is set to 1. Then the only difference is that I replace n_i with (n_i+1)... and allows p_hat to be calculated with n_i = 0. I made no attempt to handle UCTdelta, but replacing n_i in there with n_i+n_h is probably reasonable On 5/17/07, Chaslot G (MICC) <[EMAIL PROTECTED]> wrote:
Dear all, Following the example of Rémi, I would like to share with you a paper that I wrote which describe some important elements of my Go program Mango. I submitted this paper recently to the JCIS workshop 2007. Due to the fact that it was an extended abstract, a lot of details are missing. I am now working on the full paper, which will contain much more information. The extended abstract can be found here: www.cs.unimaas.nl/g.chaslot/papers/pMCTS.pdf Cheers, Guillaume PS: To answer's Sylvain question: Modifying the probability distribution of moves in the tree was more effective in Mango than the improvement done on the simulation strategy. However, Mango simulation strategy is not as good as CrazyStone's or Mogo's one. So I guess Mango won against Mogo in the last KGS tournament because it had a better way to use domain knowledge in the Tree. _______________________________________________ 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/
