def trial(gene):
field = Field()
for i in range(PREY_NUM):
field.add_prey()
weights_ih, weights_ho = decoder(gene)
field.set_agent(BaselineAgent(10, 10, weights_ih, weights_ho))
for i in range(400):
field.one_step_action()
return field.agent.total_reword
def TestAuto():
field = Field()
for i in range(PREY_NUM):
field.add_prey()
field.set_agent(BaselineAgent(10, 10))
for i in range(400):
os.system('clear')
draw(field)
field.one_step_action()
print(field.agent.total_reword)
def TestManual():
field = Field()
for i in range(PREY_NUM):
field.add_prey()
field.set_agent(BaselineAgent(10, 10))
while (True):
os.system('clear')
draw(field)
input_vector = field.give_input_vector()
print(input_vector)
c = input('action: ')
if c == 'g':
action_no = 0
elif c == 'j':
action_no = 1
elif c == 'r':
action_no = 2
elif c == 'l':
action_no = 3
field.position_update(action_no)
def trial(gene):
#learning_process(don't use reword)
toy_field = ToyField()
for i in range(PREY_NUM):
toy_field.add_prey()
weights_ih, weights_ho, weights_im, weights_mh, weights_em = decoder(
gene) #need to fix
toy_field.set_agent(
MainAgent(10, 10, weights_ih, weights_ho, weights_im, weights_mh,
weights_em))
for i in range(800):
toy_field.one_step_action()
#trial_process(use reword)
field = Field()
for i in range(PREY_NUM):
field.add_prey()
field.set_agent(toy_field.hand_over_agent())
for i in range(400):
field.one_step_action()
return field.agent.total_reword
