def sample_strategy_from_mixed(env, str_set, mix_str, identity):
if not isinstance(mix_str,np.ndarray):
raise ValueError("mix_str in sample func is not a numpy array.")
if not len(str_set) == len(mix_str):
raise ValueError("Length of mixed strategies does not match number of strategies.")
picked_str = np.random.choice(str_set,p=mix_str)
if not fp.isInName('.pkl', name = picked_str):
raise ValueError('The strategy picked is not a pickle file.')
if identity == 0: # pick a defender's strategy
path = DIR + 'defender_strategies/'
elif identity == 1:
path = DIR + 'attacker_strategies/'
else:
raise ValueError("identity is neither 0 or 1!")
if not fp.isExist(path + picked_str):
raise ValueError('The strategy picked does not exist!')
#TODO: assign nn info from game
act = deepq.learn(
env,
network=models.mlp(num_hidden=256, num_layers=1),
total_timesteps=0,
load_path= path + picked_str
)
return act
def gambit_analysis(timeout):
if not fp.isExist(gambit_DIR):
raise ValueError(".nfg file does not exist!")
command_str = "gambit-lcp -q " + os.getcwd(
) + "/gambit_data/payoffmatrix.nfg > " + os.getcwd(
) + "/gambit_data/nash.txt"
subproc.call_and_wait_with_timeout(command_str, timeout)
def load_json_data(json_file):
'''
Loads the data from the file as Json into a new object.
'''
if not fp.isExist(DIR_json + json_file):
raise ValueError(DIR_json + json_file + " does not exist.")
with open(DIR_json + json_file) as data_file:
result = json.load(data_file)
return result
def add_def_str(self, str_name):
if not fp.isExist(self.dir_def + str_name):
raise ValueError("This strategy does not exist.")
if '_def' not in str_name:
raise ValueError("This may not be a defender's strategy due to no def sign")
if not isinstance(str_name,str):
raise ValueError("The name to be added is not a str." )
self.def_str.append(str_name)
print(str_name + " has been added to defender's strategy set")
def sample_both_strategies(env, att_str_set, att_mix_str, def_str_set, def_mix_str):
if not len(att_str_set) == len(att_mix_str):
raise ValueError("Length of mixed strategies does not match number of strategies for the attacker.")
if not len(def_str_set) == len(def_mix_str):
raise ValueError("Length of mixed strategies does not match number of strategies for the defender.")
att_picked_str = np.random.choice(att_str_set, p=att_mix_str)
def_picked_str = np.random.choice(def_str_set, p=def_mix_str)
if not fp.isInName('.pkl', name=def_picked_str):
raise ValueError('The strategy picked is not a pickle file for the defender.')
if not fp.isInName('.pkl', name=att_picked_str):
raise ValueError('The strategy picked is not a pickle file for the attacker.')
path_def = DIR + 'defender_strategies/'
path_att = DIR + 'attacker_strategies/'
if not fp.isExist(path_def + def_picked_str):
raise ValueError('The strategy picked does not exist for the defender!')
if not fp.isExist(path_att + att_picked_str):
raise ValueError('The strategy picked does not exist for the attacker!')
act_att = deepq.learn(
env,
network=models.mlp(num_hidden=256, num_layers=1),
total_timesteps=0,
load_path=path_att + att_picked_str
)
act_def = deepq.learn(
env,
network=models.mlp(num_hidden=256, num_layers=1),
total_timesteps=0,
load_path= path_def + def_picked_str
)
return act_att, act_def
def decode_gambit_file():
nash_DIR = os.getcwd() + '/gambit_data/nash.txt'
if not fp.isExist(nash_DIR):
raise ValueError("nash.txt file does not exist!")
with open(nash_DIR, 'r') as f:
nash = f.readline()
if len(nash.strip()) == 0:
return 0, 0
nash = nash[3:]
nash = nash.split(',')
new_nash = []
for i in range(len(nash)):
new_nash.append(convert(nash[i]))
new_nash = np.array(new_nash)
new_nash = np.round(new_nash, decimals=2)
nash_def = new_nash[:int(len(new_nash) / 2)]
nash_att = new_nash[int(len(new_nash) / 2):]
return nash_att, nash_def