def __init__(self, grid, goalVals, discount=.99, tau=.01, epsilon=.001):
MDP.__init__(self, discount=discount, tau=tau, epsilon=epsilon)
self.goalVals = goalVals
self.grid = grid
self.setGridWorld()
self.valueIteration()
self.extractPolicy()
def __init__(self, grid, goalVals, discount=.99, tau=.01, epsilon=.001): MDP.__init__(self, discount=discount, tau=tau, epsilon=epsilon) self.goalVals = goalVals self.grid = grid self.setGridWorld() self.valueIteration() self.extractPolicy()
def __init__(self, grid, terminals, init=(0, 0), gamma=.9):
MDP.__init__(self, init, actlist=orientations, terminals=terminals, gamma=gamma)
grid.reverse() ## because we want row 0 on bottom, not on top
self.grid=grid
self.rows=len(grid)
self.cols=len(grid[0])
for x in range(self.cols):
for y in range(self.rows):
self.reward[x, y] = grid[y][x] # each reward is from the grid
if grid[y][x] is not None:
self.states.add((x, y)) # each state is a tuple of indices
def __init__(self, grid, terminals, init=(0, 0), gamma=.9):
MDP.__init__(self,
init,
actlist=orientations,
terminals=terminals,
gamma=gamma)
self.grid = grid
self.rows = len(grid)
self.cols = len(grid[0])
# print(self.rows,self.cols)
for x in range(self.cols):
for y in range(self.rows):
self.reward[y, x] = grid[y][x]
if self.state_check((y, x)):
self.states.add((y, x))