def __init__(self):
self.random = MyRand(123)
self.round = 0
self.players_money = [0] * get_players()
self.sumof_bit_bellow_values = 0 # sum of all bit_below_values that won
self.behaviours = {
1: [
0, self.allin
], # first value is the winning counter of this behaviour in the specific auction.
0.5: [0, self.halfin],
"not specific value": [0, self.bit_below],
0: [0, self.zero]
}
class NoTieBot:
def __init__(self):
self.players_money = [0] * get_players()
self.random = MyRand(123)
def play_round(self, winner, win_amount):
self.players_money = [d + get_dollars() for d in self.players_money]
if winner == -10:
self.players_money[self.random.randint(1,
get_players() -
1)] -= win_amount
elif winner != -1:
self.players_money[winner] -= win_amount
if self.players_money[0] in self.players_money[1:]:
return self.players_money[0] - self.random.randint(1, 10)
return self.players_money[0]
class BitBelowBot:
def __init__(self):
self.dollar = 0
self.random = MyRand(123)
def play_round(self, winner, win_amount):
self.dollar += get_dollars()
if winner == 0:
self.dollar -= win_amount
return self.dollar - self.random.randint(0, min(20, get_dollars()))
class RandomBot:
def __init__(self):
self.dollar = 0
self.random = MyRand(1)
def play_round(self, winner, win_amount):
self.dollar += get_dollars()
if winner == 0:
self.dollar -= win_amount
return self.random.randint(0, self.dollar)
def __init__(self):
self.dollar = 0
self.random = MyRand(123)
class SelectiveBot:
# 1 means all in,0.5 means half in, 0 means biding 0 and all the other situations are "not specific value".
keys = [1, 0.5, "not specific value",
0] # keys represent the value win_amount/winner_player_money
def allin(self):
return self.players_money[0]
def halfin(self):
return self.players_money[0] / 2
def bit_below(self):
average_bit_bellow = self.sumof_bit_bellow_values / self.behaviours[
"not specific value"][0]
total_biding = self.players_money[0] - average_bit_bellow
if total_biding >= 0:
return total_biding
return self.allin(
) #all in if the budget is lower than average_bit_bellow
def zero(self):
return 0
def __init__(self):
self.random = MyRand(123)
self.round = 0
self.players_money = [0] * get_players()
self.sumof_bit_bellow_values = 0 # sum of all bit_below_values that won
self.behaviours = {
1: [
0, self.allin
], # first value is the winning counter of this behaviour in the specific auction.
0.5: [0, self.halfin],
"not specific value": [0, self.bit_below],
0: [0, self.zero]
}
def play_round(self, winner, win_amount):
self.round += 1
self.players_money = [d + get_dollars() for d in self.players_money]
if winner == -10:
print("I don't know what I am doing")
elif winner != -1:
self.winning_behaviour_inturn = win_amount / (
self.players_money[winner] - get_dollars()
) # the behaviour of the recent winner
if self.winning_behaviour_inturn != 1 and self.winning_behaviour_inturn != 0.5 and self.winning_behaviour_inturn != 0:
self.winning_behaviour_inturn = "not specific value"
self.sumof_bit_bellow_values += (
self.players_money[winner] - get_dollars()
) - win_amount # the needed bit bellow value to win
self.players_money[winner] -= win_amount
self.behaviours[self.winning_behaviour_inturn][
0] += 1 # adding 1 to the winning behaviour of this turn
if self.round == get_rounds():
return self.players_money[
0] # default all in acting if it is the final round.
max_wins = max([
self.behaviours[key][0] for key in self.keys
]) # the max_wins that have been with 1 or more behaviours
winnable_behaviours = [
] # saves all the behaviours that won max_wins times.
for key in self.keys:
if self.behaviours[key][0] == max_wins:
winnable_behaviours.append(key)
# ideally it's only one the winnable behaviour but if it isn't the chosen behaviour will be randomly.
chosen_behaviour = winnable_behaviours[self.random.randint(
0,
len(winnable_behaviours) - 1)]
return self.behaviours[chosen_behaviour][1]()
def __init__(self):
self.players_money = [0] * get_players()
self.random = MyRand(123)