pubeval evaluation

This commit is contained in:
Christoffer Müller Madsen 2018-03-12 00:11:40 +01:00
parent ac924f655b
commit 90b97da4ff
3 changed files with 42 additions and 7 deletions

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@ -24,8 +24,12 @@ command-line options and switches are listed by running =main.py= with the argum
** Evaluation methods
Currently, only a single evaluation method is implemented:
Currently, the following evaluation methods are implemented:
- =pubeval=: Evaluates against the =pubeval= backgammon benchmark developed by
Gerald Tesauro. The source code is included in the =pubeval= directory and
needs to be compiled before use. The binary should be placed at
=pubeval/pubeval=.
- =random=: Evaluates by playing against a player that makes random moves drawn
from the set of legal moves. Should be used with high episode counts to lower
variance. *TODO*: Doesn't even work currently
@ -54,9 +58,9 @@ The following examples describe commmon operations.
=python3 --eval --model-name=quack=
*** Evaluate default model using evaluation methods =random= and =foovaluation=
*** Evaluate default model using evaluation methods =random= and =pubeval=
=python3 --eval --eval-methods random foovaluation=
=python3 --eval --eval-methods random pubeval=
* Model storage format

4
bot.py
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@ -48,9 +48,9 @@ class Bot:
return random.choice(list(legal_moves))
# TODO: Test this, the score results are deterministic
# TODO: Test this, the score results should be deterministic
def make_pubeval_move(self, board, sym, roll):
legal_moves = Board.calculate_legal_states(board, sym, roll)
legal_moves = Board.calculate_legal_states(tuple(board), sym, roll)
moves_and_scores = []
for board in legal_moves:
call_argument = ["./pubeval/pubeval"]

35
game.py
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@ -6,7 +6,7 @@ from cup import Cup
import numpy as np
import sys
import time
class Game:
@ -131,10 +131,22 @@ class Game:
def eval(self, trained_eps = 0):
def do_eval(method, episodes = 1000, trained_eps = 0):
start_time = time.time()
def print_time_estimate(eps_completed):
cur_time = time.time()
time_diff = cur_time - start_time
eps_per_sec = eps_completed / time_diff
secs_per_ep = time_diff / eps_completed
eps_remaining = (episodes - eps_completed)
sys.stderr.write("[EVAL ] Averaging {per_sec} episodes per second\n".format(per_sec = round(eps_per_sec, 2)))
sys.stderr.write("[EVAL ] {eps_remaining} episodes remaining; approx. {time_remaining} seconds remaining\n".format(eps_remaining = eps_remaining, time_remaining = int(eps_remaining * secs_per_ep)))
sys.stderr.write("[EVAL ] Evaluating {eps} episode(s) with method '{method}'\n".format(eps=episodes, method=method))
if method == 'random':
outcomes = []
for i in range(episodes):
for i in range(1, episodes + 1):
sys.stderr.write("[EVAL ] Episode {}".format(i))
self.board = Board.initial_state
while Board.outcome(self.board) is None:
@ -145,10 +157,29 @@ class Game:
sys.stderr.write("\t outcome {}".format(Board.outcome(self.board)[1]))
outcomes.append(Board.outcome(self.board)[1])
sys.stderr.write("\n")
if i % 50 == 0:
print_time_estimate(i)
return outcomes
elif method == 'pubeval':
outcomes = []
# Add the evaluation code for pubeval, the bot has a method make_pubeval_move(board, sym, roll), which can be used to get the best move according to pubeval
for i in range(1, episodes + 1):
sys.stderr.write("[EVAL ] Episode {}".format(i))
self.board = Board.initial_state
while Board.outcome(self.board) is None:
roll = self.roll()
self.board = (self.p1.make_move(self.board, self.p1.get_sym(), roll))[0]
roll = self.roll()
self.board = Board.flip(self.p2.make_pubeval_move(Board.board_features_to_pubeval(self.board, self.p2.get_sym()), self.p2.get_sym(), roll)[0][0:26])
sys.stderr.write("\t outcome {}".format(Board.outcome(self.board)[1]))
outcomes.append(Board.outcome(self.board)[1])
sys.stderr.write("\n")
if i % 10 == 0:
print_time_estimate(i)
return outcomes
else:
sys.stderr.write("[EVAL ] Evaluation method '{}' is not defined\n".format(method))
return [0]