def test():
env = Environment.Env(4, 4, 0.15)
obstacles = [(1, 1), (1, 3)]
for obs in obstacles:
env.addobstacle(obs)
agent1 = Environment.agent(env)
cat1 = Environment.agent(env, autopolicy=True)
cat2 = Environment.agent(env, autopolicy=True)
with open(".\Cost1\policy_sto.pkl", "rb") as f:
policy = pickle.load(f)
mdp = MDP()
mdp.addplayer(agent1)
mdp.addplayer(cat1)
mdp.addplayer(cat2)
#Test calculate gridworld
mdp.calgridworldsp()
# for st in mdp.gridworldspace:
# print (st)
assert len(
mdp.gridworldspace) == 2744, 'gridworldspace section is not correct'
# Test calculate statespace
mdp.addpolicy(policy)
mdp.addpolicy(policy)
mdp.calstatespace()
assert len(mdp.statespace) == 5488, 'statespace section is not correct'
# Test calculate actionspace
mdp.calactionspace()
assert len(mdp.actionspace) == 2, 'actionspace 2 section is not correct'
mdp.setT(4)
mdp.calactionspace()
assert len(mdp.actionspace) == 8, 'actionspace 8 section is not correct'
mdp.termst = mdp.terminalSt()
mdp.penalty = mdp.setpenalty()
mdp.cal_Kstep_Matrix()
# stindex = mdp.invertedindex[(((1, 2), (1, 2), (2, 3)), 1)]
# stindex2 = mdp.invertedindex[(((1, 2), (1, 2), (2, 3)), 2)]
# P = mdp.transitMatrix[2][2][stindex]
# if abs(sum(P) -1) > 0.01:
# print(123)
# print(P[stindex])
# print(P[stindex2])
V, policy = mdp.valueFunc_semi(stochastic=False)
filename = ".\Cost1\V_semi_4.pkl"
file = open(filename, "wb")
pickle.dump(V, file)
file.close()
filename = ".\Cost1\policy_semi_4.pkl"
file = open(filename, "wb")
pickle.dump(policy, file)
file.close()
def test():
env = Environment.Env(4, 4, 0.15)
obstacles = [(1, 1), (1, 3)]
for obs in obstacles:
env.addobstacle(obs)
agent1 = Environment.agent(env)
cat1 = Environment.agent(env, autopolicy=True)
cat2 = Environment.agent(env, autopolicy=True)
#Choose Policy
with open(".\Revision1\policy_sto.pkl", "rb") as f:
policy_act = pickle.load(f)
with open(".\Revision1\policy_semi_2.pkl", "rb") as f:
policy = pickle.load(f)
agent_ini = (1, 0)
cat1_ini = (3, 2)
cat2_ini = (0, 3)
state = (agent_ini, cat1_ini, cat2_ini)
steplist = []
trajlist = []
sensorrewardlist = []
penaltylist = []
# for i in range(1000):
# stepcount, traj, penaltycount = simulate_2(agent1, cat1, agent_ini, cat1_ini, policy_act)
# steplist.append(stepcount)
# trajlist.append(trajlist)
# # costlist.append(cost)
# penaltylist.append(penaltycount)
for i in range(1000):
stepcount, traj, sensorreward, penaltycount = simulate_3(
agent1, cat1, cat2, state, policy, policy_act)
steplist.append(stepcount)
trajlist.append(trajlist)
sensorrewardlist.append(sensorreward)
penaltylist.append(penaltycount)
filename = ".\Revision1\steplist2.pkl"
file = open(filename, "wb")
pickle.dump(steplist, file)
file.close()
filename = ".\Revision1\\trajlist2.pkl"
file = open(filename, "wb")
pickle.dump(trajlist, file)
file.close()
print(sum(steplist) / 1000)
print(sum(sensorrewardlist) / 1000)
print(sum(penaltylist) / 1000)