def get_action(self, state):
actions = state.available_moves()
for a in actions:
if DSL.isDoubles(a) and DSL.actionWinsColumn(state,a):
self._counter_calls[0] += 1
return a
if DSL.numberPositionsConquered(state,5)>0 and DSL.containsNumber(a,4):
self._counter_calls[1] += 1
return a
if DSL.isStopAction(a) and DSL.numberPositionsConquered(state,5)>1 and DSL.containsNumber(a,6):
self._counter_calls[2] += 1
return a
if DSL.isStopAction(a) and DSL.numberPositionsProgressedThisRoundColumn(state,2)>2 and DSL.isStopAction(a):
self._counter_calls[3] += 1
return a
if DSL.isStopAction(a):
self._counter_calls[4] += 1
return a
if DSL.actionWinsColumn(state,a) and DSL.actionWinsColumn(state,a):
self._counter_calls[5] += 1
return a
if DSL.isStopAction(a):
self._counter_calls[6] += 1
return a
return actions[0]
def get_action(self, state):
actions = state.available_moves()
if DSL.isYNAction(actions):
if DSL.hasAvailableNeuralMarker(state):
return 'y'
if DSL.hasWonColumn(state):
return 'n'
if DSL.continueBecausehighProbNotBust(state):
return 'y'
return random.choice(actions)
else:
if DSL.hasAvailableNeuralMarker(state):
actions = deepcopy(DSL.actionsUseLessMarker(state, actions))
for a in actions:
if DSL.isDoubles(a):
return a
for a in actions:
if DSL.actionWinsColumn(state, a):
return a
# should be later than detect the already progressed one (use of neutral marker)
# newActions = []
# if DSL.hasAvailableNeuralMarker(state):
# for a in actions:
# if DSL.actionEasyToPrograss(state, a):
# newActions.append(a)
# if newActions:
# actions = deepcopy(newActions)
return random.choice(actions)
def get_action(self, state):
actions = state.available_moves()
print("Actions: ", actions)
for a in actions:
if DSL.actionWinsColumn(state, a):
return a
if DSL.isDoubles(a):
return a
if DSL.containsNumber(a, (6,2)):
return a
if DSL.isStopAction(a):
return a
return actions[0]
def get_action(self, state):
actions = state.available_moves()
for a in actions:
if DSL.hasWonColumn(state) and DSL.isStopAction(a):
self._counter_calls[0] += 1
return a
if DSL.actionWinsColumn(state, a):
self._counter_calls[1] += 1
return a
return actions[0]
def get_action(self, state):
actions = state.available_moves()
for a in actions:
if DSL.actionWinsColumn(state, a):
return a
if DSL.isDoubles(a):
return a
if DSL.containsNumber(a, 6) or DSL.containsNumber(a, 2):
if np.random.choice([0, 1], p=[0.6, 0.4]) > 0:
return a
if DSL.isStopAction(a):
# Return 'y' with 70% probability and 'n' with 30% probability.
if DSL.hasWonColumn(state, a):
return 'n'
else:
return 'y'
return actions[0]
def get_action(self, state):
actions = state.available_moves()
for a in actions:
if DSL.hasWonColumn(state) and DSL.isStopAction(a):
self._counter_calls[0] += 1
return a
if DSL.actionWinsColumn(state, a) and DSL.hasWonColumn(state):
self._counter_calls[1] += 1
return a
if DSL.numberPositionsConquered(
state, 5) > 2 and DSL.containsNumber(a, 4):
self._counter_calls[2] += 1
return a
return actions[0]