def get_pre(self, agent, n_census):
"""
Gathers and uses env info to make a prehension transition matrix
Args:
self: the env
agent: the agent acting in the env
n_census: unused
Returns:
prehesion based on what Creatures are North, South,
East, and West of self, determining what direction
the agent might come.
"""
trans_str = ""
d, total = self.dir_info(agent)
if (type(agent) == Zombie):
trans_str += self.zombie_trans(d, total)
else:
trans_str += self.human_trans(d, total)
trans_matrix = markov.from_matrix(np.matrix(trans_str))
return trans_matrix
def get_pre(self, agent, n_census):
numRH = 0
numBH = 0
numRF = 0
numBF = 0
if(REDHIPSTER in n_census):
numRH = n_census[REDHIPSTER]
if(BLUEHIPSTER in n_census):
numBH = n_census[BLUEHIPSTER]
if(REDFOLLOWER in n_census):
numRF = n_census[REDFOLLOWER]
if(BLUEFOLLOWER in n_census):
numBF = n_census[BLUEFOLLOWER]
rh = self.influence(numRH, 5)
bh = self.influence(numBH, 5)
rf = self.influence(numRF, 5)
bf = self.influence(numBF, 5)
str_trans = ""
# THE TRANSITION MATRIX
# See documentation.
str_trans += str(1 - rf) + " " + str(rf) + " 0 0;"
str_trans += str(bf) + " " + str(1 - bf) + " 0 0;"
str_trans += "0 0 " + str(1 - bh) + " " + str(bh) + ";"
str_trans += "0 0 " + str(rh) + " " + str(1 - rh)
trans_matrix = markov.from_matrix(np.matrix(str_trans))
return trans_matrix
def get_pre(self, agent, n_census):
"""
Gathers and uses env info to make a prehension transition matrix
Args:
self: the env
agent: the agent acting in the env
n_census: unused
Returns:
prehesion based on what Creatures are North, South,
East, and West of self, determining what direction
the agent might come.
"""
trans_str = ""
d, total = self.dir_info(agent)
if(type(agent) == Wolf):
trans_str += self.wolf_trans(d, total)
else:
trans_str += self.sheep_trans(d, total)
trans_matrix = markov.from_matrix(np.matrix(trans_str))
return trans_matrix
def get_pre(self, agent, n_census):
"""
See documentation for how this is built,
what effect it produces, and why it
produces it.
"""
trans_matrix = markov.create_iden_matrix(self.max_pile_size)
i=2
j=i
count=0.0
"""
These while loops aren't a big drag.
It makes a lower triangular matrix of size ~vlen**2,
and we ony cycle through at most 4 times in the
innermost loop.
"""
while(i<self.max_pile_size):
while(1<=j):
if(str(j) in n_census):
while(n_census(str(j))>0):
count+=1
n_census[str(j)]-=1
trans_matrix[i,j] = (count/4)**(i+1/j)
j-=1
trans_matrix[i,i]= 1 - (count/4)
i+=1
j=i
count=0
return markov.from_matrix(trans_matrix)
def __init__(self, name, width, height, trans_str=None, torus=False,
matrix_dim=2, model_nm=None, preact=False, postact=False,
mobile_agents=False, props=None):
"""
Create a new markov env. By default the transition matrix is identity.
"""
if trans_str is None:
self.def_trans_matrix = markov.from_matrix(markov.create_iden_matrix(matrix_dim))
else:
self.def_trans_matrix = markov.MarkovPre(trans_str)
super().__init__(name, width, height, torus, preact,
postact, model_nm=model_nm, props=props)
def get_pre(self, agent, n_census):
trans_str = ""
d, total = self.dir_info(agent)
if type(agent) == Zombie:
trans_str += self.zombie_trans(d, total)
else:
trans_str += self.human_trans(d, total)
trans_matrix = markov.from_matrix(np.matrix(trans_str))
return trans_matrix
def get_pre(self, agent, n_census):
trans_str = ""
d, total = self.dir_info(agent)
if type(agent) == Zombie:
trans_str += self.zombie_trans(d, total)
else:
trans_str += self.human_trans(d, total)
trans_matrix = markov.from_matrix(np.matrix(trans_str))
return trans_matrix
def __init__(self, name, goal, vlen, init_state, max_detect=1):
super().__init__(name, goal, max_move=1, max_detect=max_detect)
self.state_pre = markov.from_matrix(
markov.state_vector(vlen, init_state))
self.state = markov.get_state(markov.to_matrix(self.state_pre))