mapkoc 35 Report post Posted December 29, 2017 (edited) Hi, I adapted http://www.glicko.net/glicko/glicko.pdf to apply to raitings bot. import math # Rating deviation extrema RDmax = 140 RDmin = 40 # Linear mapping GPthr = 100 # games played threshold m = float(GPthr) / (RDmin - RDmax) # slope # Simple Glicko without rating deviation aging def get_rating_adjustment2(rating, opponent_rating, games_played, opponent_games_played, result): r = rating rj = opponent_rating sj = (result + 1) / 2 # outcome # Linear mapping of games played to rating deviation # instead of RD = min(math.sqrt(RD_{old}^2 + c^2), 350) RD = RDmin if games_played > GPthr else m * games_played + RDmax RDj = RDmin if opponent_games_played > GPthr else m * opponent_games_played + RDmax # Rating delta q = math.log(10) / 400 gj = 1 / math.sqrt(1 + 3 * math.pow(q * RDj / math.pi, 2)) Ej = 1 / (1 + math.pow(10, gj * (rj - r) / 400)) d2 = 1 / (math.pow(q * gj, 2) * Ej * (1 - Ej)) value = 1 / RD / RD + 1 / d2 # RDnew = math.sqrt(1 / value) # not used for now return round(q * gj * (sj - Ej) / value) It has 3 parameters that control how much a player gains or loses depending on its experience. The rating deviation (RD) is like the standard deviation and states the certainty of a player's rating and determines how much a result influences rating. To fit current code, I modified the algorithm to linearly assign RD \in [RDmax, RDmin] according to games played \in [0, GPthr] and RDmin if games played > GPthr With RDmax = 140 so inexperienced players dont jump too much, RDmin = 40 so experienced players can still slowly increase rating, and arbitrarily setting maximum experience with GPthr = 100 games played, we can test with from random import choice, seed, randint r1,r2 = 2100, 1200 seed() for x in range(GPthr+10): print(r1, r2) res = choice([-1, 1]) #r1 += get_rating_adjustment(r1, randint(1100, 2100), GPthr+x, randint(0, GPthr), 1) r1 += get_rating_adjustment2(r1, r2, GPthr+x, 0+x, res) r2 += get_rating_adjustment2(r2, r1, 0+x, GPthr+x, -res) print(r1, r2) Test 1: expert player like borg vs new player, 110 games with 50-50% wins You can see how with Glicko the expert is not greatly affected but possible smurfs. Test 2: Average fully experienced player always winning vs all kinds of players The original rating was pretty certain but RDmin gives chance for improvement, quite slowly. Fics uses a variation of the algorithm: http://www.freechess.org/Help/HelpFiles/glicko.html Edited December 29, 2017 by mapkoc 1 Share this post Link to post Share on other sites

Lion.Kanzen 2,210 Report post Posted December 30, 2017 (edited) My bad , wrong ,,post... Edited December 30, 2017 by Lion.Kanzen Share this post Link to post Share on other sites