# DESCRIPTION of PLAYERS.
# weights[0] determines how important size of a piece is
# weights[1] determines how important maximizing the difference of my corners and opponent corners
# weights[2] decides how many of the best placements we choose to look ahead with
# weights[3] decides how important the score of the second move is
# weights[4] decides how important the score of the first move is
# <EDIT START
NUM_ITERATION = 20
SAVE_FILE_NAME = "min_v_greedy_%d.json" % NUM_ITERATION
DEBUG = False
# EDIT END/>
### RUN & SAVE ###
record_dicts = []
for i in range(NUM_ITERATION):
print("################ Iteration %d ################" % (i+1) )
# <EDIT START
first = Greedy("A", "Minimax(2,1)A", Minimax_Player, [2, 1, 5, 1, 1])
second = Player("B", "RandomB", Random_Player)
third = Greedy("C", "Greedy(2,1)C", Greedy_Player, [2, 1, 5, 1, 1])
fourth = Player("D", "RandomD", Random_Player)
# EDIT END/>
record_dicts += [T.run_test_all_general(first, second, third, fourth,DEBUG)]
T.save(record_dicts, SAVE_FILE_NAME)
import sys import os cwd = os.getcwd() sys.path.insert(0, cwd + "/..") import test_utils as T # not random any more. all_random = "all_random.json" greedy_v_greedy_5 = "greedy[2,1]_v_greedy[2,1]_5.json" greedy_v_greedy_15 = "greedy[2,1]_v_greedy[2,1]_15.json" min_v_greedy_20 = "min[2,1]_v_greedy[2,1]_20.json" FILENAME1 = greedy_v_greedy_5 FILENAME2 = greedy_v_greedy_15 loaded1 = T.load(FILENAME1) loaded2 = T.load(FILENAME2) T.save(loaded1 + loaded2, "greedy[2,1]_v_greedy[2,1]_20.json")
import sys\nsys.path.insert(0, '/Users/minyoungjeong/Desktop/4511_project/Machine-Learning-Blokus-master') import test_utils as T result = T.run_test_all_random(True) T.save([result], "test.json")
# Run four random players.
NUM_ITERATION = 2
import sys
sys.path.insert(
0,
'/Users/minyoungjeong/Desktop/4511_project/Machine-Learning-Blokus-master')
import test_utils as T
record_dicts = []
for i in range(NUM_ITERATION):
record_dicts += [T.run_test_all_random()]
T.save(record_dicts, "all_random.json")