def move(self):
possible_steps = movement_control.find_empty_location(self.pos, self.model)
#select new position based on cow behavior algorithm from Multi Agent Programming Contest
new_position = self.cow_behavior(possible_steps)
if (new_position is not None):
self.model.grid.move_agent(self, new_position)
def move(self):
prev_pos = self.pos
#possible_steps = movement_control.find_empty_location(self.pos, self.model)
#new_position = random.choice(possible_steps)
#self.model.grid.move_agent(self, new_position)
if (self.current_plan_step == self.LOOKFORCOW):
print("finding cow to follow")
self.cow_to_follow = self.find_free_cow_in_radius()
if (self.cow_to_follow is not None):
print("found cow")
self.current_plan_step = self.HERDCOW
else:
# Move randomly to find a cow
print("no cow here, keep looking")
possible_steps = movement_control.find_empty_location(
self.pos, self.model)
new_position = random.choice(possible_steps)
self.model.grid.move_agent(self, new_position)
elif (self.current_plan_step == self.HERDCOW):
if not self.cow_to_follow: # if no cow to follow, go back to looking
self.current_plan_step = self.LOOKFORCOW
elif self.cow_to_follow.pos in self.model.goalState: # cow is already in goal
print("cow is in the goal - resetting")
self.current_plan_step = self.LOOKFORCOW
self.cow_to_follow = None
else:
# herd the cow!
print("herding cow")
self.move_to_herding_location()
if prev_pos == self.pos: # if hasn't moved, might be stuck, move randomly
possible_steps = movement_control.find_empty_location(
self.pos, self.model)
new_position = random.choice(possible_steps)
self.model.grid.move_agent(self, new_position)
def move(self):
possible_steps = movement_control.find_empty_location(
self.pos, self.model)
new_position = random.choice(possible_steps)
#print(self.unique_id, " moving from ", self.pos, " to ", new_position)
self.model.grid.move_agent(self, new_position)
def move(self):
# if was following a cow and it entered the goal, stop following it
if(self.cow_to_follow):
if self.cow_to_follow.pos in self.model.goalState: # cow is already in goal
print("followed cow is in the goal - resetting")
self.cow_to_follow = None
self.need_new_action = True
if(self.need_new_action):
print("Picking a new action")
possible_actions = []
# decide possible actions
# if not at the goal space
#if(not((self.pos[0] == self.model.goalTarget[0]) and (self.pos[1] == self.model.goalTarget[1]))):
# possible_actions.append(self.TOWARDSGOAL)
# if have a target cow and more than one cow in the radius
neighbors = self.model.grid.get_neighbors(self.pos, moore = True, include_center=False, radius= self.vision_radius)
cows_in_radius = cow_methods.find_neighbor_cows(neighbors)
if(self.cow_to_follow and (len(cows_in_radius) > 0)):
possible_actions.append(self.HERDTOGETHER)
# if have a target cow, can head towards it, flank it, or herd it towards the goal
if(self.cow_to_follow):
# possible_actions.extend([self.TOWARDSCOW, self.FLANK, self.HERDCOW, self.BLOCK])
possible_actions.extend([self.TOWARDSCOW, self.FLANK, self.HERDCOW]) # Remove block if cows can't escape
else: #no cow to follow, find one
possible_actions.append(self.LOOKFORCOW)
# Choose an action
print("possible actions are ", possible_actions)
self.current_plan_step = random.choice(possible_actions)
if (self.current_plan_step == self.LOOKFORCOW): # Find a cow
print("finding cow to follow")
self.cow_to_follow = self.find_free_cow_in_radius()
if (self.cow_to_follow is not None):
print("found cow")
#self.current_plan_step = self.HERDCOW
self.need_new_action = True
else:
# Move randomly to find a cow
print("no cow here, keep looking")
possible_steps = movement_control.find_empty_location(self.pos, self.model)
new_position = random.choice(possible_steps)
self.model.grid.move_agent(self, new_position)
elif (self.current_plan_step == self.HERDCOW): # herd a cow towards the goal
print("herding cow to goal")
if not self.cow_to_follow: # if no cow to follow
print("no cow to follow")
#self.current_plan_step = self.LOOKFORCOW
self.need_new_action = True
elif self.cow_to_follow.pos in self.model.goalState: # cow is already in goal
print("cow is in the goal - resetting")
#self.current_plan_step = self.LOOKFORCOW
self.cow_to_follow = None
self.need_new_action = True
else:
# herd the cow
print("herding cow")
self.move_to_herding_location()
elif (self.current_plan_step == self.FLANK):
print("flanking cow")
if not self.cow_to_follow: # if no cow to follow
print("no cow to flank")
self.need_new_action = True
if (random.randint(0, 4) == 0): # don't want to flank forever
print("not flanking anymore")
self.need_new_action = True
else:
self.flank_cow()
elif (self.current_plan_step == self.HERDTOGETHER):
print("herding cows together")
if not self.cow_to_follow: # if no cow to follow
print("no cow to herd")
self.need_new_action = True
elif not self.cow_to_herd_towards:
print("CHOOSE SECONDARY COW")
self.choose_secondary_cow()
if not self.cow_to_herd_towards:
self.need_new_action = True
self.herd_cows_together()
else:
self.herd_cows_together()
elif (self.current_plan_step == self.TOWARDSCOW): #take a step towards a cow
print("one step towards cow")
if not self.cow_to_follow: # if no cow to follow
self.need_new_action = True
else:
prev_pos = self.pos
movement_control.move_towards(self, self.cow_to_follow.pos)
if(self.pos == prev_pos): # tried to move towards the cow but it didn't work
print("Can't move towards cow, moving randomly")
possible_steps = movement_control.find_empty_location(self.pos, self.model)
new_position = random.choice(possible_steps)
self.need_new_action = True
elif (self.current_plan_step == self.BLOCK):
# don't want to block forever, chance to break out of block
if (random.randint(0, 4) == 0):
print("not blocking anymore")
self.need_new_action = True
else:
print("block")
self.block()
elif (self.current_plan_step == self.TOWARDSGOAL):
# if not at the goal space
if((self.pos[0] == self.model.goalTarget[0]) and (self.pos[1] == self.model.goalTarget[1])):
print("already at goal")
self.need_new_action = True
else:
print("moving towards goal")
movement_control.move_towards(self, self.model.goalTarget)
else:
print("No more available actions, choose again")
self.need_new_action = True