Python GridWorld示例

示例#1

def prob(p):
    p = float(p)
    n = 1.0 - p
    return {
        'S': (('S', p), ('N', n)),
        'N': (('N', p), ('S', n)),
        'E': (('E', p), ('W', n)),
        'W': (('W', p), ('E', n)),
    }


STATES = ((0, 3), (0, 2), (1, 2), (0, 1), (1, 1), (0, 0))

if __name__ == '__main__':
    print "\nInitial values:"
    g = GridWorld(GRID, prob(1), STATES, 1, -4)
    print g

    i = g.value_iteration(0.1)
    print "\nValues after %d iterations:" % i
    print g

    g = GridWorld(GRID, prob(0.8), STATES, 1, -4)
    print "\nValue of (1,2) after first iteration: %.1f" % g.value(0, 3)

    g = GridWorld(GRID, prob(0.8), STATES, 1, -4)
    i = g.value_iteration(0.1)
    print "\nValues after %d iterations:" % i
    print g

示例#2

文件： example_2.py 项目： SunLinJie/Artificial-Intelligence-and-Machine-Learning

from MDP.grid import GridWorld

GRID = [[0, 0, 0, 0], [-100, 0, 0, 100]]


def prob(p):
    p = float(p)
    n = 1.0 - p
    return {"S": (("S", p), ("N", n)), "N": (("N", p), ("S", n)), "E": (("E", p), ("W", n)), "W": (("W", p), ("E", n))}


STATES = ((0, 3), (0, 2), (1, 2), (0, 1), (1, 1), (0, 0))

if __name__ == "__main__":
    print "\nInitial values:"
    g = GridWorld(GRID, prob(1), STATES, 1, -4)
    print g

    i = g.value_iteration(0.1)
    print "\nValues after %d iterations:" % i
    print g

    g = GridWorld(GRID, prob(0.8), STATES, 1, -4)
    print "\nValue of (1,2) after first iteration: %.1f" % g.value(0, 3)

    g = GridWorld(GRID, prob(0.8), STATES, 1, -4)
    i = g.value_iteration(0.1)
    print "\nValues after %d iterations:" % i
    print g

示例#3

文件： example_1.py 项目： neozhangthe1/AI--ML--Robotics-...

from MDP.grid import GridWorld

GRID = [[0,    0, 0,  100],
        [0, None, 0, -100],
        [0,    0, 0,    0]]

PROB = {
    'S':(('S', 0.8), ('W', 0.1), ('E', 0.1)),
    'N':(('N', 0.8), ('E', 0.1), ('W', 0.1)),
    'E':(('E', 0.8), ('S', 0.1), ('N', 0.1)),
    'W':(('W', 0.8), ('N', 0.1), ('S', 0.1)),
}

STATES = ((0,2),(0,1),(1,2),(0,0),(2,2),(1,0),(2,1),(2,0),(2,3))

if __name__ == '__main__':
    g = GridWorld(GRID, PROB, STATES, 1, -3)
    v = g.value(0,2)
    print "\nValue of (0,2) after first iteration: %.1f" % v
    g.grid[0][2] = v
    print "\nValue of (1,2) after first iteration: %.1f" % g.value(1,2)
    
    print "\nInitial values:"
    g = GridWorld(GRID, PROB, STATES, 1, -3)
    print g
    
    i = g.value_iteration(0.1)
    print "\nValues after %d iterations:" % i
    print g

示例#4

文件： midterm.py 项目： 01010000101001100/Artificial-Intelligence-and-Machine-Learning

).satisfiability_report()
print Proposition(
    lambda a, b, c: (implies(a, b) or implies(b, c)) == implies(a, c),
                    "((a => b) and (b => c)) == (a => c)"
).satisfiability_report()


print "\n=== Problem 14 ==="
from MDP.grid import GridWorld
GRID = [[0, 0, None, 100],
        [0, 0,    0,   0]]

PROB = {
    'S':(('S', 1.0), ),
    'N':(('N', 1.0), ),
    'E':(('E', 1.0), ),
    'W':(('W', 1.0), ),
}

STATES = ((1,3),(1,2),(1,1),(0,1),(1,0),(0,0))
g = GridWorld(GRID, PROB, STATES, 1, -5)
i = g.value_iteration(0.1)
print "Values after %d iterations:" % i
print g

print "\n=== Problem 15 ==="
from Markov.markov import TransProb
TRANSITIONS = [("A","A","A","A","B")]
t = TransProb(TRANSITIONS)
t.report(k=1)

示例#5

文件： midterm.py 项目： neozhangthe1/AI--ML--Robotics-...

print Proposition(lambda a, b, c: implies(a, b) and (not ((not a) or b)),
                  "(a => b) and (not ((not a) or b))").satisfiability_report()
print Proposition(
    lambda a, b, c: (implies(a, b) or implies(b, c)) == implies(a, c),
    "((a => b) and (b => c)) == (a => c)").satisfiability_report()

print "\n=== Problem 14 ==="
from MDP.grid import GridWorld

GRID = [[0, 0, None, 100], [0, 0, 0, 0]]

PROB = {
    'S': (('S', 1.0), ),
    'N': (('N', 1.0), ),
    'E': (('E', 1.0), ),
    'W': (('W', 1.0), ),
}

STATES = ((1, 3), (1, 2), (1, 1), (0, 1), (1, 0), (0, 0))
g = GridWorld(GRID, PROB, STATES, 1, -5)
i = g.value_iteration(0.1)
print "Values after %d iterations:" % i
print g

print "\n=== Problem 15 ==="
from Markov.markov import TransProb

TRANSITIONS = [("A", "A", "A", "A", "B")]
t = TransProb(TRANSITIONS)
t.report(k=1)