value_iteration_gridworld.py

import numpy as np
from env.grid_world import GridWorld, GridWorldVisualization
from tabular_methods.dynamic_programming import ValueIteration

# nrows = 4
# ncols = 4
# start_state = (0, 0)
# goal_state = (3, 3)
# obstacles = [(1, 1),(0, 2)]

# hard grid
nrows = 20
ncols = 20
start_state = (0, 0)
goal_state = (19, 19)
obstacles = [(5, 5), (5, 6), (5, 7), (5, 8), (5, 9),
             (6, 9), (7, 9), (8, 9), (9, 9), (10, 9),
             (10, 8), (10, 7), (10, 6), (10, 5), (10, 4),
             (11, 4), (12, 4), (13, 4), (14, 4), (15, 4),
             (15, 5), (15, 6), (15, 7), (15, 8), (15, 9),
             (16, 9), (17, 9), (18, 9), (19, 9), (19, 10)]

grid_world = GridWorld(nrows, ncols, start_state, goal_state)
grid_world.add_obstacles(obstacles)
grid_world.add_rewards(-1.0, 100.0)
grid_world.dynamics() 
policy = grid_world.random_policy()

# Policy Iteration:
V, policy = ValueIteration(grid_world, theta=0.0001)

# Visualization results:
visualization = GridWorldVisualization(grid_world)
visualization.plot_grid_with_arrows(grid_world, policy, fig_name="value_iteration_gridworld")