def __init__(self,
initial_state=INI_STATE,
additional_predicates=(),
background=(),
block_n=4,
all_block=False):
actions = [MOVE]
self.max_step = 50
self._block_encoding = {
"a": 1,
"b": 2,
"c": 3,
"d": 4,
"e": 5,
"f": 6,
"g": 7
}
self.state_dim = MAX_WIDTH**3
if all_block:
self._all_blocks = list(
string.ascii_lowercase)[:MAX_WIDTH] + ["floor"]
else:
self._all_blocks = list(
string.ascii_lowercase)[:block_n] + ["floor"]
self.language = LanguageFrame(actions,
extensional=[ON, FLOOR, TOP] +
list(additional_predicates),
constants=self._all_blocks)
self._additional_predicates = additional_predicates
background = list(background)
background.append(Atom(FLOOR, ["floor"]))
# background.extend([Atom(BLOCK, [b]) for b in list(string.ascii_lowercase)[:block_n]])
super(BlockWorld, self).__init__(background, initial_state, actions)
self._block_n = block_n
def __init__(self, width=3, know_valid_pos=True):
actions = [PLACE]
self.language = LanguageFrame(actions, extensional=[ZERO, MINE, EMPTY, OPPONENT, SUCC],
constants=[str(i) for i in range(width)])
background = []
#background.extend([Atom(LESS, [str(i), str(j)]) for i in range(0, WIDTH)
# for j in range(0, WIDTH) if i < j])
background.extend([Atom(SUCC, [str(i), str(i + 1)]) for i in range(width - 1)])
background.append(Atom(ZERO, ["0"]))
self.max_step = 50
initial_state = np.zeros([3,3])
super(TicTacTeo, self).__init__(background, initial_state, actions)
self.width = width
self.all_positions = [(i, j) for i in range(width) for j in range(width)]
self.know_valid_pos = know_valid_pos
self.action_n = len(self.all_positions)
self.state_dim = width**2
class TicTacTeo(SymbolicEnvironment):
all_variations = ("n")
def __init__(self, width=3, know_valid_pos=True,case = []):
actions = [PLACE]
self.language = LanguageFrame(actions, extensional=[ZERO, MINE, EMPTY, OPPONENT, SUCC],
constants=[str(i) for i in range(width)])
background = []
#background.extend([Atom(LESS, [str(i), str(j)]) for i in range(0, WIDTH)
# for j in range(0, WIDTH) if i < j])
background.extend([Atom(SUCC, [str(i), str(i + 1)]) for i in range(width - 1)])
background.append(Atom(ZERO, ["0"]))
self.max_step = 50
initial_state = np.zeros([3,3])
self.case = case
#init = np.zeros([3,3])
if len(case)==0:
initial_state = np.zeros([3,3])
def __init__(self, initial_state=("0", "0"), width=5):
actions = [UP, DOWN, LEFT, RIGHT]
self.language = LanguageFrame(actions, extensional=[ZERO, SUCC, CURRENT, LAST],
constants=[str(i) for i in range(width)])
background = []
self.unseen_background = []
self.unseen_background.extend([Atom(CLIFF, [str(x), "0"]) for x in range(1, width - 1)])
self.unseen_background.append(Atom(GOAL, [str(width - 1), "0"]))
background.append(Atom(LAST, [str(width - 1)]))
#background.extend([Atom(CLIFF, [str(x), "0"]) for x in range(1, WIDTH-1)])
#background.extend([Atom(LESS, [str(i), str(j)]) for i in range(0, width)
# for j in range(0, width) if i < j])
background.extend([Atom(SUCC, [str(i), str(i+1)]) for i in range(width - 1)])
background.append(Atom(ZERO, ["0"]))
#background.extend([Atom(CLIFF, ["1", str(y)]) for y in range(2, WIDTH)])
#background.extend([Atom(CLIFF, ["3", str(y)]) for y in range(1, WIDTH-1)])
super(CliffWalking, self).__init__(background, initial_state, actions)
self.max_step = 50
self.state_dim = 2
self.all_actions = actions
self.width=width