Functions.create_random_obstacles(grid_world, 0.105)
grid_world.scan_grid_and_generate_graph()
grid_world.print_graph()
grid_world.create_grid_ui(grid_world.m, grid_world.n,
(grid_world.start_x, grid_world.start_y),
(grid_world.end_x, grid_world.end_y),
grid_world.obstacles)
SA = SARSAgent(list(range(4)))
scores, episodes = [], []
number_of_episodes = 1000
for episode in range(number_of_episodes):
score = 0
state = grid_world.reset()
grid_world.is_visited = [[0] * grid_world.m
for temp in range(grid_world.n)]
while True:
grid_world.render()
action = SA.get_action(str(state))
next_state, reward, done = grid_world.step(action)
next_action = SA.get_action(str(next_state))
SA.learn(str(state), action, reward, str(next_state), next_action)
print("<state:{0} , action:{1} , reward:{2} , next_state:{3}>".
format(str(state), str(action), str(reward),
str(next_state)))
# grid_world.is_visited[state[0]][state[1]] += 1
state = next_state
action = next_action
score += reward
