def bid(self, t, history, reserve):
# The Balanced bidding strategy (BB) is the strategy for a player j that, given
# bids b_{-j},
# - targets the slot s*_j which maximizes his utility, that is,
# s*_j = argmax_s {clicks_s (v_j - t_s(j))}.
# - chooses his bid b' for the next round so as to
# satisfy the following equation:
# clicks_{s*_j} (v_j - t_{s*_j}(j)) = clicks_{s*_j-1}(v_j - b')
# (p_x is the price/click in slot x)
# If s*_j is the top slot, bid the value v_j
prev_round = history.round(t - 1)
(slot, min_bid, max_bid) = self.target_slot(t, history, reserve)
# TODO: Fill this in.
bid = 0 # change this
# not expecting to win
if min_bid > self.value:
bid = self.value
# otherwise
elif slot != 0:
# ratio of ctr is the same as ratio of positional effect
bid = self.value - (ctr(t, slot) /
ctr(t, slot - 1)) * (self.value -
(min_bid + 1))
else:
bid = self.value
# pjh: we've got the target, just need to choose bid to
# satsify the equation above
# if t == 47:
# print("New Agent:")
# print(self.id)
# print(t)
# print(history.agents_spent[self.id])
# print()
return bid
def expected_utils(self, t, history, reserve):
"""
Figure out the expected utility of bidding such that we win each
slot, assuming that everyone else keeps their bids constant from
the previous round.
returns a list of utilities per slot.
"""
info = self.slot_info(t, history, reserve)
utilities = map(lambda j: ctr(t,j)*(self.value - ( info[j][1] + 1 ) ), range(len(info)))
return utilities
def bid(self, t, history, reserve):
# The Balanced bidding strategy (BB) is the strategy for a player j that, given
# bids b_{-j},
# - targets the slot s*_j which maximizes his utility, that is,
# s*_j = argmax_s {clicks_s (v_j - t_s(j))}.
# - chooses his bid b' for the next round so as to
# satisfy the following equation:
# clicks_{s*_j} (v_j - t_{s*_j}(j)) = clicks_{s*_j-1}(v_j - b')
# (p_x is the price/click in slot x)
# If s*_j is the top slot, bid the value v_j
prev_round = history.round(t-1)
(slot, min_bid, max_bid) = self.target_slot(t, history, reserve)
# TODO: Fill this in.
bid = 0 # change this
# not expecting to win
if min_bid > self.value:
bid = self.value
# otherwise
elif slot != 0:
# ratio of ctr is the same as ratio of positional effect
bid = self.value - ( ctr(t,slot)/ctr(t,slot-1) ) * ( self.value - (min_bid + 1) )
else:
bid = self.value
# pjh: we've got the target, just need to choose bid to
# satsify the equation above
# if t == 47:
# print("New Agent:")
# print(self.id)
# print(t)
# print(history.agents_spent[self.id])
# print()
return bid
def expected_utils(self, t, history, reserve):
"""
Figure out the expected utility of bidding such that we win each
slot, assuming that everyone else keeps their bids constant from
the previous round.
returns a list of utilities per slot.
"""
info = self.slot_info(t, history, reserve)
utilities = map(lambda j: ctr(t, j) * (self.value - (info[j][1] + 1)),
range(len(info)))
return utilities
import base64
import util
s = base64.b64decode('L77na/nrFsKvynd6HzOoG7GHTLXsTVu9qvY/2syLXzhPweyyMTJULu/6/kXX0KSvoOLSFQ==')
print(util.ctr(s, b'YELLOW SUBMARINE').decode())
import base64
import util
s = base64.b64decode(
'L77na/nrFsKvynd6HzOoG7GHTLXsTVu9qvY/2syLXzhPweyyMTJULu/6/kXX0KSvoOLSFQ==')
print(util.ctr(s, b'YELLOW SUBMARINE').decode())