class QBot(Player):
def __init__(self, numDice, name):
super().__init__(numDice, name)
self.action = Action()
self.model = QLearning(self.action, self.action.get_all_actions(), 0.9,
0.1)
self.strategy = EpsilonGreedyExploration(0.2, 0.01)
def takeBet(self, state):
a = explore(self.strategy, self.model,
state.prev_state.generateNumber(), state)
bet = self.action.get_bet(a)
if bet[0] == -1:
return "no"
else:
return " ".join(str(element) for element in list(bet))
class SavedQBot(Player):
def __init__(self, numDice, name):
super().__init__(numDice, name)
self.action = Action()
self.model = QLearning(self.action, self.action.get_all_actions(), 0.9,
0.1)
q_function = collections.defaultdict(float)
with open("qfunction_vs_saved_q_2.txt", 'r') as f:
lines = f.readlines()
for line in lines:
s, a, q_value = line.split()
q_function[(s, a)] = q_value
self.model.Q = q_function
def takeBet(self, state):
a = find_best_action(self.model, state.prev_state.generateNumber(),
state)
bet = self.action.get_bet(a)
if bet[0] == -1:
return "no"
else:
return " ".join(str(element) for element in list(bet))
