def __init__(self, mission_file=None, quest_file=None):
self.logger = logging.getLogger(__name__)
if False: # True if you want to see more information
self.logger.setLevel(logging.DEBUG)
else:
self.logger.setLevel(logging.INFO)
self.logger.handlers = []
self.logger.addHandler(logging.StreamHandler(sys.stdout))
self.move_actions = ["movenorth 1", "movesouth 1", "movewest 1", "moveeast 1"]
self.learner = DeepQLearner(
input_size= (world_bounds[1][0]-world_bounds[0][0]+1)
+ (world_bounds[1][1]-world_bounds[0][1]+1)
+ len(logicalActions) + len(triggers),
num_actions=len(self.move_actions) + len(logicalActions),
load_path='cache/dqn.pkl',
save_path='cache/dqn.pkl',
verbose=False)
self.canvas = None
self.root = None
goal = [(Proposition("in", [itemVars['diamond'], boundary1Var]), True),
(Proposition("in", [itemVars['diamond'], inventoryVar]), True)]
self.host = LogicalAgentHost(mission_file, quest_file, logicalActions, goal, triggers, world_bounds)
self.gamma = 0.9
def test_is_sequence_applicable():
state = State([
Proposition.parse("at(P, r_1: r)"),
Proposition.parse("empty(r_2: r)"),
Proposition.parse("empty(r_3: r)"),
])
assert state.is_sequence_applicable([
Action.parse(
"go :: at(P, r_1: r) & empty(r_2: r) -> at(P, r_2: r) & empty(r_1: r)"
),
Action.parse(
"go :: at(P, r_2: r) & empty(r_3: r) -> at(P, r_3: r) & empty(r_2: r)"
),
])
assert not state.is_sequence_applicable([
Action.parse(
"go :: at(P, r_1: r) & empty(r_2: r) -> at(P, r_2: r) & empty(r_1: r)"
),
Action.parse(
"go :: at(P, r_1: r) & empty(r_3: r) -> at(P, r_3: r) & empty(r_1: r)"
),
])
assert not state.is_sequence_applicable([
Action.parse(
"go :: at(P, r_2: r) & empty(r_3: r) -> at(P, r_3: r) & empty(r_2: r)"
),
Action.parse(
"go :: at(P, r_3: r) & empty(r_1: r) -> at(P, r_1: r) & empty(r_3: r)"
),
])
def test_is_sequence_applicable():
state = State(KnowledgeBase.default().logic, [
Proposition.parse("at(P, r_1: r)"),
Proposition.parse("empty(r_2: r)"),
Proposition.parse("empty(r_3: r)"),
])
assert state.is_sequence_applicable([
Action.parse(
"go :: at(P, r_1: r) & empty(r_2: r) -> at(P, r_2: r) & empty(r_1: r)"
),
Action.parse(
"go :: at(P, r_2: r) & empty(r_3: r) -> at(P, r_3: r) & empty(r_2: r)"
),
])
assert not state.is_sequence_applicable([
Action.parse(
"go :: at(P, r_1: r) & empty(r_2: r) -> at(P, r_2: r) & empty(r_1: r)"
),
Action.parse(
"go :: at(P, r_1: r) & empty(r_3: r) -> at(P, r_3: r) & empty(r_1: r)"
),
])
assert not state.is_sequence_applicable([
Action.parse(
"go :: at(P, r_2: r) & empty(r_3: r) -> at(P, r_3: r) & empty(r_2: r)"
),
Action.parse(
"go :: at(P, r_3: r) & empty(r_1: r) -> at(P, r_1: r) & empty(r_3: r)"
),
])
def test_going_through_door():
P = Variable("P", "P")
room = Variable("room", "r")
kitchen = Variable("kitchen", "r")
state = State(KnowledgeBase.default().logic)
state.add_facts([
Proposition("at", [P, room]),
Proposition("north_of", [kitchen, room]),
Proposition("free", [kitchen, room]),
Proposition("free", [room, kitchen]),
Proposition("south_of", [room, kitchen])
])
options = ChainingOptions()
options.backward = True
options.max_depth = 3
options.max_length = 3
options.subquests = True
options.create_variables = True
options.rules_per_depth = [
[KnowledgeBase.default().rules["take/c"], KnowledgeBase.default().rules["take/s"]],
KnowledgeBase.default().rules.get_matching("go.*"),
[KnowledgeBase.default().rules["open/d"]],
]
chains = list(get_chains(state, options))
assert len(chains) == 18
def test_parallel_quests():
logic = GameLogic.parse("""
type foo {
rules {
do_a :: not_a(foo) & $not_c(foo) -> a(foo);
do_b :: not_b(foo) & $not_c(foo) -> b(foo);
do_c :: $a(foo) & $b(foo) & not_c(foo) -> c(foo);
}
constraints {
a_or_not_a :: a(foo) & not_a(foo) -> fail();
b_or_not_b :: b(foo) & not_b(foo) -> fail();
c_or_not_c :: c(foo) & not_c(foo) -> fail();
}
}
""")
kb = KnowledgeBase(logic, "")
state = State(kb.logic, [
Proposition.parse("a(foo)"),
Proposition.parse("b(foo)"),
Proposition.parse("c(foo)"),
])
options = ChainingOptions()
options.backward = True
options.kb = kb
options.max_depth = 3
options.max_breadth = 1
options.max_length = 3
chains = list(get_chains(state, options))
assert len(chains) == 2
options.max_breadth = 2
chains = list(get_chains(state, options))
assert len(chains) == 3
options.min_breadth = 2
chains = list(get_chains(state, options))
assert len(chains) == 1
assert len(chains[0].actions) == 3
assert chains[0].nodes[0].depth == 2
assert chains[0].nodes[0].breadth == 2
assert chains[0].nodes[0].parent == chains[0].nodes[2]
assert chains[0].nodes[1].depth == 2
assert chains[0].nodes[1].breadth == 1
assert chains[0].nodes[1].parent == chains[0].nodes[2]
assert chains[0].nodes[2].depth == 1
assert chains[0].nodes[2].breadth == 1
assert chains[0].nodes[2].parent is None
options.min_breadth = 1
options.create_variables = True
state = State(kb.logic)
chains = list(get_chains(state, options))
assert len(chains) == 5
def test_state():
state = State()
P = Variable.parse("P")
kitchen = Variable.parse("kitchen: r")
study = Variable.parse("study: r")
stove = Variable.parse("stove: o")
at_kitchen = Proposition.parse("at(P, kitchen: r)")
in_kitchen = Proposition.parse("in(stove: o, kitchen: r)")
at_study = Proposition.parse("at(P, study: r)")
assert not state.is_fact(at_kitchen)
assert not state.is_fact(in_kitchen)
assert not state.is_fact(at_study)
assert len(state.variables) == 0
assert len(state.variables_of_type("P")) == 0
assert len(state.variables_of_type("r")) == 0
assert len(state.variables_of_type("o")) == 0
state.add_fact(at_kitchen)
state.add_fact(in_kitchen)
assert state.is_fact(at_kitchen)
assert state.is_fact(in_kitchen)
assert not state.is_fact(at_study)
assert set(state.variables) == {P, kitchen, stove}
assert state.variables_of_type("P") == {P}
assert state.variables_of_type("r") == {kitchen}
assert state.variables_of_type("o") == {stove}
state.remove_fact(at_kitchen)
assert not state.is_fact(at_kitchen)
assert state.is_fact(in_kitchen)
assert not state.is_fact(at_study)
assert set(state.variables) == {kitchen, stove}
assert len(state.variables_of_type("P")) == 0
assert state.variables_of_type("r") == {kitchen}
assert state.variables_of_type("o") == {stove}
state.remove_fact(in_kitchen)
assert not state.is_fact(at_kitchen)
assert not state.is_fact(in_kitchen)
assert not state.is_fact(at_study)
assert len(state.variables) == 0
assert len(state.variables_of_type("P")) == 0
assert len(state.variables_of_type("r")) == 0
assert len(state.variables_of_type("o")) == 0
state.add_fact(at_study)
assert not state.is_fact(at_kitchen)
assert not state.is_fact(in_kitchen)
assert state.is_fact(at_study)
assert set(state.variables) == {P, study}
assert state.variables_of_type("P") == {P}
assert state.variables_of_type("r") == {study}
assert len(state.variables_of_type("o")) == 0
def main():
args = parse_args()
P = Variable("P")
# I = Variable("I")
room = Variable("room", "r")
kitchen = Variable("kitchen", "r")
state = [
Proposition("at", [P, room]),
Proposition("north_of", [kitchen, room]),
Proposition("free", [kitchen, room]),
Proposition("free", [room, kitchen]),
Proposition("south_of", [room, kitchen])
]
# Sample quests.
rng = np.random.RandomState(args.seed)
chains = []
# rules_per_depth = {0: [data.get_rules()["take/c"], data.get_rules()["take/s"]],
# 1: [data.get_rules()["open/c"]],
# }
rules_per_depth = {
0: [data.get_rules()["eat"]],
1: data.get_rules().get_matching("take/s.*"),
2: data.get_rules().get_matching("go.*"),
3: [data.get_rules()["open/d"]],
4: [data.get_rules()["unlock/d"]],
5: data.get_rules().get_matching("take/s.*", "take/c.*")
}
for i in range(args.nb_quests):
chain = textworld.logic.sample_quest(state,
rng,
max_depth=args.quest_length,
allow_partial_match=True,
exceptions=[],
rules_per_depth=rules_per_depth,
backward=True)
chains.append(chain[::-1])
print_chains(chains, verbose=args.verbose)
actions_tree = build_tree_from_chains(chains)
# Convert tree to networkx graph/tree
filename = "sample_tree.svg"
G, labels = actions_tree.to_networkx()
if len(G) > 0:
tree = nx.bfs_tree(G, actions_tree.no)
save_graph_to_svg(tree, labels, filename, backward=True)
else:
try:
os.remove(filename)
except:
pass
def __parseFacts(self, r):
f = []
for p in r:
temp = []
for v in p["vars"]:
temp.append(self.__parseVariables(v))
for cbn in itertools.product(*temp):
if "negate" in p.keys():
f.append((Proposition(p["name"], list(cbn)), not p["negate"]))
else:
f.append(Proposition(p["name"], list(cbn)))
return f
def test_backward_chaining():
P = Variable("P", "P")
room = Variable("room", "r")
kitchen = Variable("kitchen", "r")
state = State([
Proposition("at", [P, room]),
Proposition("north_of", [kitchen, room]),
Proposition("south_of", [room, kitchen]),
])
rules_per_depth = {
0: [data.get_rules()["take/c"],
data.get_rules()["take/s"]],
1: [data.get_rules()["open/c"]]
}
tree_of_possible = chaining.get_chains(state,
max_depth=2,
allow_partial_match=True,
exceptions=['d'],
rules_per_depth=rules_per_depth,
backward=True)
chains = list(tree_of_possible.traverse_preorder(subquests=True))
assert len(chains) == 3
for chain in chains:
for depth, action in enumerate(chain):
assert action.action.name in [
rule.name for rule in rules_per_depth[depth]
]
rules_per_depth = {
0: [data.get_rules()["put"]],
1: [data.get_rules()["go/north"]],
2: [data.get_rules()["take/c"]]
}
tree_of_possible = chaining.get_chains(state,
max_depth=3,
allow_partial_match=True,
exceptions=['d'],
rules_per_depth=rules_per_depth,
backward=True)
chains = list(tree_of_possible.traverse_preorder(subquests=True))
assert len(chains) == 3
for chain in chains:
for depth, action in enumerate(chain):
assert action.action.name in [
rule.name for rule in rules_per_depth[depth]
]
def test_get_visible_objects_in():
P = Variable("P")
room = Variable("room", "r")
chest = Variable("chest", "c")
obj = Variable("obj", "o")
# Closed chest.
facts = [Proposition("at", [P, room]),
Proposition("at", [chest, room]),
Proposition("in", [obj, chest]),
Proposition("closed", [chest])]
world = World.from_facts(facts)
objects = world.get_visible_objects_in(world.player_room)
assert obj in world.objects
assert obj not in objects
# Open chest.
facts = [Proposition("at", [P, room]),
Proposition("at", [chest, room]),
Proposition("in", [obj, chest]),
Proposition("open", [chest])]
world = World.from_facts(facts)
objects = world.get_visible_objects_in(world.player_room)
assert obj in world.objects
assert obj in objects
def test_get_objects_in_inventory():
P = Variable("P")
I = Variable("I")
room = Variable("room", "r")
obj = Variable("obj", "o")
# Closed chest.
facts = [Proposition("at", [P, room]),
Proposition("in", [obj, I])]
world = World.from_facts(facts)
objects = world.get_objects_in_inventory()
assert obj in world.objects
assert obj in objects
def test_populate_with():
# setup
P = Variable('P')
I = Variable('I')
room = Variable('room', 'r')
facts = [Proposition('at', [P, room])]
world = World.from_facts(facts)
# test
obj = Variable('obj', 'o')
world.populate_with(objects=[obj])
assert obj in world.objects
assert (Proposition('at', [obj, room]) in world.facts or Proposition('in', [obj, I]) in world.facts)
def check_state(state):
fail = Proposition("fail", [])
debug = Proposition("debug", [])
constraints = state.all_applicable_actions(data.get_constraints().values())
for constraint in constraints:
if state.is_applicable(constraint):
# Optimistically delay copying the state
copy = state.copy()
copy.apply(constraint)
if copy.is_fact(fail):
return False
return True
def test_going_through_door():
P = Variable("P", "P")
room = Variable("room", "r")
kitchen = Variable("kitchen", "r")
state = State()
state.add_facts([
Proposition("at", [P, room]),
Proposition("north_of", [kitchen, room]),
Proposition("free", [kitchen, room]),
Proposition("free", [room, kitchen]),
Proposition("south_of", [room, kitchen])
])
# Sample quests.
chains = []
rules_per_depth = {
0: [data.get_rules()["take/c"],
data.get_rules()["take/s"]],
1: data.get_rules().get_matching("go.*"),
2: [data.get_rules()["open/d"]]
}
tree_of_possible = chaining.get_chains(state,
max_depth=3,
allow_partial_match=True,
exceptions=[],
rules_per_depth=rules_per_depth,
backward=True)
chains = list(tree_of_possible.traverse_preorder(subquests=True))
# chaining.print_chains(chains)
# 1. take/c(P, room, c_0, o_0, I)
# 2. take/c(P, room, c_0, o_0, I) -> go/north(P, r_0, room)
# 3. take/c(P, room, c_0, o_0, I) -> go/north(P, r_0, room) -> open/d(P, r_0, d_0, room)
# 4. take/c(P, room, c_0, o_0, I) -> go/south(P, kitchen, room)
# 5. take/c(P, room, c_0, o_0, I) -> go/south(P, kitchen, room) -> open/d(P, kitchen, d_0, room)
# 6. take/c(P, room, c_0, o_0, I) -> go/east(P, r_0, room)
# 7. take/c(P, room, c_0, o_0, I) -> go/east(P, r_0, room) -> open/d(P, r_0, d_0, room)
# 8. take/c(P, room, c_0, o_0, I) -> go/west(P, r_0, room)
# 9. take/c(P, room, c_0, o_0, I) -> go/west(P, r_0, room) -> open/d(P, r_0, d_0, room)
# 10. take/s(P, room, s_0, o_0, I)
# 11. take/s(P, room, s_0, o_0, I) -> go/north(P, r_0, room)
# 12. take/s(P, room, s_0, o_0, I) -> go/north(P, r_0, room) -> open/d(P, r_0, d_0, room)
# 13. take/s(P, room, s_0, o_0, I) -> go/south(P, kitchen, room)
# 14. take/s(P, room, s_0, o_0, I) -> go/south(P, kitchen, room) -> open/d(P, kitchen, d_0, room)
# 15. take/s(P, room, s_0, o_0, I) -> go/east(P, r_0, room)
# 16. take/s(P, room, s_0, o_0, I) -> go/east(P, r_0, room) -> open/d(P, r_0, d_0, room)
# 17. take/s(P, room, s_0, o_0, I) -> go/west(P, r_0, room)
# 18. take/s(P, room, s_0, o_0, I) -> go/west(P, r_0, room) -> open/d(P, r_0, d_0, room)
assert len(chains) == 18
def set_winning_conditions(
self,
winning_conditions: Optional[Collection[Proposition]]) -> Action:
""" Sets wining conditions for this quest.
Args:
winning_conditions: Set of propositions that need to be true
before marking the quest as completed.
Default: postconditions of the last action.
Returns:
An action that is only applicable when the quest is finished.
"""
if winning_conditions is None:
if len(self.actions) == 0:
raise UnderspecifiedQuestError()
# The default winning conditions are the postconditions of the
# last action in the quest.
winning_conditions = self.actions[-1].postconditions
# TODO: Make win propositions distinguishable by adding arguments?
win_fact = Proposition("win")
self.win_action = Action("win",
preconditions=winning_conditions,
postconditions=list(winning_conditions) +
[win_fact])
return self.win_action
def _convert_to_needs_relation(proposition):
if not proposition.name.startswith("needs_"):
return proposition
return Proposition("needs",
[proposition.arguments[0],
Variable(proposition.name.split("needs_")[-1], "STATE")])
def setUpClass(cls):
M = GameMaker()
# The goal
commands = ["go east", "insert carrot into chest"]
# Create a 'bedroom' room.
R1 = M.new_room("bedroom")
R2 = M.new_room("kitchen")
M.set_player(R1)
path = M.connect(R1.east, R2.west)
path.door = M.new(type='d', name='wooden door')
path.door.add_property("open")
carrot = M.new(type='f', name='carrot')
M.inventory.add(carrot)
# Add a closed chest in R2.
chest = M.new(type='c', name='chest')
chest.add_property("open")
R2.add(chest)
cls.failing_conditions = (Proposition("eaten", [carrot.var]),)
cls.quest = M.set_quest_from_commands(commands)
cls.quest.set_failing_conditions(cls.failing_conditions)
cls.game = M.build()
def set_conditions(self, conditions: Iterable[Proposition]) -> Action:
"""
Set the triggering conditions for this event.
Args:
conditions: Set of propositions which need to
be all true in order for this event
to get triggered.
Returns:
Action that can only be applied when all conditions are statisfied.
"""
if not conditions:
if len(self.actions) == 0:
raise UnderspecifiedEventError()
# The default winning conditions are the postconditions of the
# last action in the quest.
conditions = self.actions[-1].postconditions
variables = sorted(set([v for c in conditions for v in c.arguments]))
event = Proposition("event", arguments=variables)
self.condition = Action("trigger",
preconditions=conditions,
postconditions=list(conditions) + [event])
return self.condition
def inventory_proposition(observation, objectVars, inventoryVar):
updated_props = set()
inventory = observation['inventory']
for item in inventory:
key = item['type']
updated_props.add(
Proposition("in", [Variable.parse(key), inventoryVar]))
return updated_props
def test_logic_parsing():
P = Variable("P", "P")
kitchen = Variable("kitchen", "r")
egg = Variable("egg", "f")
assert Variable.parse("P") == P
assert Variable.parse("kitchen: r") == kitchen
at_kitchen = Proposition("at", [P, kitchen])
in_kitchen = Proposition("in", [egg, kitchen])
raw_egg = Proposition("raw", [egg])
cooked_egg = Proposition("cooked", [egg])
assert Proposition.parse("at(P, kitchen: r)") == at_kitchen
assert Signature.parse("at(P, r)") == at_kitchen.signature
cook_egg = Action("cook", [at_kitchen, in_kitchen, raw_egg],
[at_kitchen, in_kitchen, cooked_egg])
assert Action.parse(
"cook :: $at(P, kitchen: r) & $in(egg: f, kitchen: r) & raw(egg: f) -> cooked(egg: f)"
) == cook_egg
P = Placeholder("P", "P")
r = Placeholder("r", "r")
d = Placeholder("d", "d")
rp = Placeholder("r'", "r")
assert Placeholder.parse("P") == P
assert Placeholder.parse("r") == r
assert Placeholder.parse("d") == d
assert Placeholder.parse("r'") == rp
at_r = Predicate("at", [P, r])
link = Predicate("link", [r, d, rp])
unlocked = Predicate("unlocked", [d])
at_rp = Predicate("at", [P, rp])
assert Predicate.parse("link(r, d, r')") == link
go = Rule("go", [at_r, link, unlocked], [link, unlocked, at_rp])
assert Rule.parse(
"go :: at(P, r) & $link(r, d, r') & $unlocked(d) -> at(P, r')") == go
# Make sure the types match in the whole expression
assert_raises(ValueError, Rule.parse,
"take :: $at(P, r) & $in(c, r) & in(o: k, c) -> in(o, I)")
def test_used_names_is_updated(verbose=False):
# Make generation throughout the framework reproducible.
g_rng.set_seed(1234)
# Generate a map that's shape in a cross with room0 in the middle.
P = Variable('P')
r = Variable('r_0', 'r')
k1 = Variable('k_1', 'k')
k2 = Variable('k_2', 'k')
c1 = Variable('c_1', 'c')
c2 = Variable('c_2', 'c')
facts = [
Proposition('at', [P, r]),
Proposition('at', [k1, r]),
Proposition('at', [k2, r]),
Proposition('at', [c1, r]),
Proposition('at', [c2, r]),
Proposition('match', [k1, c1]),
Proposition('match', [k2, c2])
]
world = World.from_facts(facts)
world.set_player_room() # Set start room to the middle one.
world.populate_room(10,
world.player_room) # Add objects to the starting room.
# Generate the world representation.
grammar = textworld.generator.make_grammar({},
rng=np.random.RandomState(42))
game = textworld.generator.make_game_with(world, [], grammar)
for entity_infos in game.infos.values():
if entity_infos.name is None:
continue
assert entity_infos.name in grammar.used_names
def new_fact(self, name: str, *entities: List["WorldEntity"]) -> None:
""" Create new fact.
Args:
name: The name of the new fact.
*entities: A list of entities as arguments to the new fact.
"""
args = [entity.var for entity in entities]
return Proposition(name, args)
def test_cannot_automatically_positioning_rooms():
P = Variable("P")
r0 = Variable("Room0", "r")
r1 = Variable("Room1", "r")
r2 = Variable("Room2", "r")
r3 = Variable("Room3", "r")
r4 = Variable("Room4", "r")
r5 = Variable("Room5", "r")
d = Variable("door", "d")
facts = [Proposition("at", [P, r0])]
facts.extend(connect(r0, 'north', r1))
facts.extend(connect(r0, 'east', r2))
facts.extend(connect(r0, 'south', r3))
facts.extend(connect(r0, 'west', r4))
world = World.from_facts(facts)
npt.assert_raises(NoFreeExitError, world.add_fact, Proposition("link", [r0, d, r5]))
def test_automatically_positioning_rooms():
P = Variable("P")
r1 = Variable("Room1", "r")
r2 = Variable("Room2", "r")
d = Variable("door", "d")
facts = [Proposition("at", [P, r1])]
world = World.from_facts(facts)
assert len(world.rooms) == 1
assert len(world.find_room_by_id(r1.name).exits) == 0
world.add_fact(Proposition("link", [r1, d, r2]))
assert len(world.rooms) == 2
r1_entity = world.find_room_by_id(r1.name)
r2_entity = world.find_room_by_id(r2.name)
assert len(r1_entity.exits) == 1
assert len(r2_entity.exits) == 1
assert list(r1_entity.exits.keys())[0] == reverse_direction(list(r2_entity.exits.keys())[0])
def get_human_readable_fact(self, fact: Proposition) -> Proposition:
def _get_name(info):
return info.name if info.name else info.id
arguments = [
Variable(_get_name(self.entity_infos[var.name]), var.type)
for var in fact.arguments
]
return Proposition(fact.name, arguments)
def reconstitute_facts(facts_list):
if not isinstance(facts_list[0],
Proposition): # maybe serialized list of facts
# world_facts0 = world_facts.copy()
facts_list = [
Proposition.deserialize(fact_json) for fact_json in facts_list
]
# print("Deserialized:\n", facts_list, "\n===>\n", facts_list)
return facts_list
def add_fact(self, name: str, *entities: List["WorldEntity"]) -> None:
""" Adds a fact to this entity.
Args:
name: The name of the new fact.
*entities: A list of entities as arguments to the new fact.
"""
args = [entity.var for entity in entities]
self._facts.append(Proposition(name, args))
def test_backward_chaining():
P = Variable("P", "P")
room = Variable("room", "r")
kitchen = Variable("kitchen", "r")
state = State(KnowledgeBase.default().logic, [
Proposition("at", [P, room]),
Proposition("north_of", [kitchen, room]),
Proposition("south_of", [room, kitchen]),
])
options = ChainingOptions()
options.backward = True
options.max_depth = 2
options.max_length = 2
options.subquests = True
options.create_variables = True
options.rules_per_depth = [
[
KnowledgeBase.default().rules["take/c"],
KnowledgeBase.default().rules["take/s"]
],
[KnowledgeBase.default().rules["open/c"]],
]
options.restricted_types = {"d"}
chains = list(get_chains(state, options))
assert len(chains) == 3
options = ChainingOptions()
options.backward = True
options.max_depth = 3
options.max_length = 3
options.subquests = True
options.create_variables = True
options.rules_per_depth = [
[KnowledgeBase.default().rules["put"]],
[KnowledgeBase.default().rules["go/north"]],
[KnowledgeBase.default().rules["take/c"]],
]
options.restricted_types = {"d"}
chains = list(get_chains(state, options))
assert len(chains) == 3
def _atom2proposition(atom):
if isinstance(atom, fast_downward.translate.pddl.conditions.Atom):
if atom.predicate == "=":
return None
return Proposition(
atom.predicate,
[Variable(arg, name2type[arg]) for arg in atom.args])
elif isinstance(atom,
fast_downward.translate.pddl.f_expression.Assign):
if atom.fluent.symbol == "total-cost":
return None
#name = "{}_{}".format(atom.fluent.symbol, atom.expression.value)
name = "{}".format(atom.expression.value)
return Proposition(
name,
[Variable(arg, name2type[arg]) for arg in atom.fluent.args])
def format_facts(facts_list, prev_action=None, obs_descr=None, kg=None):
if not isinstance(facts_list[0], Proposition): # maybe serialized list of facts
# world_facts0 = world_facts.copy()
facts_list = [Proposition.deserialize(fact_json) for fact_json in facts_list]
if kg is None:
kg = KnowledgeGraph(None, debug=False) # suppress excessive print() outs
kg.update_facts(facts_list, prev_action=prev_action)
#return str(kg)
return kg.describe_room(kg.player_location.name, obs_descr=obs_descr)
