def extend_mutexes(mutexes, task, atoms, actions):
atoms = common.filter_atoms(atoms)
pairs = gen_all_pairs(mutexes)
if len(pairs) == 0:
return set(), set()
actions = [ExtendAction(x, atoms) for x in actions]
spurious = SpuriousDetector(actions)
spurious.set_spurious(pairs)
facts = { x : ExtendFact(x, pairs, actions) for x in atoms }
candidates = gen_all_pairs([atoms]) - pairs
init = set(task.init) & atoms
candidates -= gen_all_pairs([init])
candidates = set([frozenset([facts[x] for x in y]) for y in candidates])
candidates_size = 0
while candidates_size != len(candidates):
candidates_size = len(candidates)
for cand in list(candidates):
pair = frozenset([x.fact for x in cand])
if spurious.exist(pair):
continue
c1, c2 = cand
if c1.check(c2) and c2.check(c1):
spurious.set_spurious([pair])
pairs.add(pair)
candidates.remove(cand)
c1.add_mutex(c2)
c2.add_mutex(c1)
return pairs, set()
def full(task, atoms, actions, verbose = False, max_states = -1):
atoms = common.filter_atoms(atoms)
init = set(task.init) & atoms
actions = [FullAction(a, atoms) for a in actions]
unreached_facts = set(atoms)
unreached_pairs = common.gen_all_pairs([atoms])
reached_states = set()
states = set([frozenset(init)])
while len(states) > 0:
#print(reached_states)
next_states = set()
for s in states:
for a in actions:
action_apply(a, s, next_states)
unreached_facts -= s
unreached_pairs -= common.gen_all_pairs([s])
reached_states.add(s)
states = next_states - reached_states
if verbose:
print('mutex.full():: Reached states:', len(reached_states))
if max_states >= 0 and len(reached_states) > max_states:
print('mutex.full():: Exceeded max-states ({0}/{1}). Aborted.'
.format(len(reached_states), max_states))
return None, None
mutexes = unreached_pairs
return mutexes, unreached_facts
def rfa_conflict_bind(task, atoms, actions):
atoms = common.filter_atoms(atoms)
atom_to_fact = { a : RFAFact(a, atoms) for a in atoms }
facts = atom_to_fact.values()
actions = [RFAAction(a, atoms, atom_to_fact) for a in actions]
[(f.set_all_facts(facts), f.set_actions(actions)) for f in facts]
rfa_init(atom_to_fact, task, atoms, actions)
change = True
while change:
change = False
for f in facts:
change |= f.apply_transitivity()
change |= f.check_useless()
change |= f.check_actions()
return facts
def rfa_conflict_bind(task, atoms, actions):
atoms = common.filter_atoms(atoms)
atom_to_fact = {a: RFAFact(a, atoms) for a in atoms}
facts = atom_to_fact.values()
actions = [RFAAction(a, atoms, atom_to_fact) for a in actions]
[(f.set_all_facts(facts), f.set_actions(actions)) for f in facts]
rfa_init(atom_to_fact, task, atoms, actions)
change = True
while change:
change = False
for f in facts:
change |= f.apply_transitivity()
change |= f.check_useless()
change |= f.check_actions()
return facts
def h2(task, atoms, actions):
atoms = common.filter_atoms(atoms)
actions = [H2Action(a, atoms) for a in actions]
init = set(task.init) & atoms
reached1 = init
reached2 = common.gen_all_pairs([init])
lastsize = 0
while len(reached1) + len(reached2) != lastsize:
lastsize = len(reached1) + len(reached2)
for a in actions:
if a.pre1.issubset(reached1) and a.pre2.issubset(reached2):
r1, r2 = a.eff(reached1, reached2)
reached1 |= r1
reached2 |= r2
m2 = common.gen_all_pairs([atoms]) - reached2
return m2, atoms - reached1
def h2(task, atoms, actions):
atoms = common.filter_atoms(atoms)
actions = [H2Action(a, atoms) for a in actions]
init = set(task.init) & atoms
reached1 = init
reached2 = common.gen_all_pairs([init])
lastsize = 0
while len(reached1) + len(reached2) != lastsize:
lastsize = len(reached1) + len(reached2)
for a in actions:
if a.pre1.issubset(reached1) and a.pre2.issubset(reached2):
r1, r2 = a.eff(reached1, reached2)
reached1 |= r1
reached2 |= r2
m2 = common.gen_all_pairs([atoms]) - reached2
return m2, atoms - reached1
def fa(task, atoms, actions, rfa=False, rfa_bind_conflict=None):
atoms = common.filter_atoms(atoms)
atoms_dict, atoms_list = common.create_atoms_dict(atoms)
ilp = cplex.Cplex()
ilp.objective.set_sense(ilp.objective.sense.maximize)
ilp.set_log_stream(None)
ilp.set_error_stream(None)
ilp.set_results_stream(None)
ilp.set_warning_stream(None)
ilp.parameters.tune_problem([(ilp.parameters.threads, 1)])
ilp.variables.add(obj=[1. for x in atoms_list],
names=[str(x) for x in atoms_list],
types=['B' for x in atoms_list])
# Initial state constraint
s_init = list(set(task.init) & atoms)
constr = cplex.SparsePair(ind=[atoms_dict[x] for x in s_init],
val=[1. for _ in s_init])
ilp.linear_constraints.add(lin_expr=[constr], senses=['L'], rhs=[1.])
# Action constraints
for action in actions:
pre = set(action.precondition) & atoms
add_eff = set([x[1] for x in action.add_effects]) & atoms
del_eff = set([x[1] for x in action.del_effects]) & atoms
pre = [atoms_dict[x] for x in pre if not x.negated]
add_eff = [atoms_dict[x] for x in add_eff]
del_eff = [atoms_dict[x] for x in del_eff]
if len(add_eff) == 0:
continue
pre_del = list(set(pre) & set(del_eff))
constr = cplex.SparsePair(ind=add_eff + pre_del,
val=[1. for _ in add_eff] +
[-1. for _ in pre_del])
ilp.linear_constraints.add(lin_expr=[constr], senses=['L'], rhs=[0.])
if rfa:
constr2 = cplex.SparsePair(ind=pre_del, val=[1. for _ in pre_del])
ilp.linear_constraints.add(lin_expr=[constr2],
senses=['L'],
rhs=[1.])
# Bind and conflict set constraints
if rfa_bind_conflict is not None:
for f in rfa_bind_conflict:
if f in f.conflict:
constr = cplex.SparsePair(ind=[atoms_dict[f.fact]], val=[1.])
ilp.linear_constraints.add(lin_expr=[constr],
senses=['E'],
rhs=[0.])
continue
if len(f.bind) > 1:
bind = [atoms_dict[x.fact] for x in f.bind - set([f])]
cbind = cplex.SparsePair(ind=bind + [atoms_dict[f.fact]],
val=[-1. for _ in bind] + [len(bind)])
ilp.linear_constraints.add(lin_expr=[cbind],
senses=['L'],
rhs=[0.])
confl = [atoms_dict[x.fact] for x in f.conflict]
cconfl = cplex.SparsePair(ind=confl + [atoms_dict[f.fact]],
val=[1. for _ in confl] + [len(confl)])
ilp.linear_constraints.add(lin_expr=[cconfl],
senses=['L'],
rhs=[len(confl)])
mutexes = set()
ilp.solve()
#print(c.solution.get_status())
while ilp.solution.get_status() == 101:
values = ilp.solution.get_values()
if sum(values) <= 1.5:
break
sol = [atoms_list[x] for x in range(len(values)) if values[x] > 0.5]
mutexes.add(frozenset(sol))
# Add constraint removing all subsets of the current solution
constr_idx = [x for x in range(len(values)) if values[x] < 0.5]
constr = cplex.SparsePair(ind=constr_idx, val=[1. for _ in constr_idx])
ilp.linear_constraints.add(lin_expr=[constr], senses=['G'], rhs=[1.])
ilp.solve()
return mutexes, set()
def fa(task, atoms, actions, rfa = False, rfa_bind_conflict = None):
atoms = common.filter_atoms(atoms)
atoms_dict, atoms_list = common.create_atoms_dict(atoms)
ilp = cplex.Cplex()
ilp.objective.set_sense(ilp.objective.sense.maximize)
ilp.set_log_stream(None)
ilp.set_error_stream(None)
ilp.set_results_stream(None)
ilp.set_warning_stream(None)
ilp.parameters.tune_problem([(ilp.parameters.threads, 1)])
ilp.variables.add(obj = [1. for x in atoms_list],
names = [str(x) for x in atoms_list],
types = ['B' for x in atoms_list])
# Initial state constraint
s_init = list(set(task.init) & atoms)
constr = cplex.SparsePair(ind = [atoms_dict[x] for x in s_init],
val = [1. for _ in s_init])
ilp.linear_constraints.add(lin_expr = [constr], senses = ['L'], rhs = [1.])
# Action constraints
for action in actions:
pre = set(action.precondition) & atoms
add_eff = set([x[1] for x in action.add_effects]) & atoms
del_eff = set([x[1] for x in action.del_effects]) & atoms
pre = [atoms_dict[x] for x in pre if not x.negated]
add_eff = [atoms_dict[x] for x in add_eff]
del_eff = [atoms_dict[x] for x in del_eff]
if len(add_eff) == 0:
continue
pre_del = list(set(pre) & set(del_eff))
constr = cplex.SparsePair(ind = add_eff + pre_del,
val = [1. for _ in add_eff]
+ [-1. for _ in pre_del])
ilp.linear_constraints.add(lin_expr = [constr],
senses = ['L'], rhs = [0.])
if rfa:
constr2 = cplex.SparsePair(ind = pre_del, val = [1. for _ in pre_del])
ilp.linear_constraints.add(lin_expr = [constr2],
senses = ['L'], rhs = [1.])
# Bind and conflict set constraints
if rfa_bind_conflict is not None:
for f in rfa_bind_conflict:
if f in f.conflict:
constr = cplex.SparsePair(ind = [atoms_dict[f.fact]], val = [1.])
ilp.linear_constraints.add(lin_expr = [constr],
senses = ['E'], rhs = [0.])
continue
if len(f.bind) > 1:
bind = [atoms_dict[x.fact] for x in f.bind - set([f])]
cbind = cplex.SparsePair(ind = bind + [atoms_dict[f.fact]],
val = [-1. for _ in bind] + [len(bind)])
ilp.linear_constraints.add(lin_expr = [cbind],
senses = ['L'], rhs = [0.])
confl = [atoms_dict[x.fact] for x in f.conflict]
cconfl = cplex.SparsePair(ind = confl + [atoms_dict[f.fact]],
val = [1. for _ in confl] + [len(confl)])
ilp.linear_constraints.add(lin_expr = [cconfl],
senses = ['L'], rhs = [len(confl)])
mutexes = set()
ilp.solve()
#print(c.solution.get_status())
while ilp.solution.get_status() == 101:
values = ilp.solution.get_values()
if sum(values) <= 1.5:
break
sol = [atoms_list[x] for x in range(len(values)) if values[x] > 0.5]
mutexes.add(frozenset(sol))
# Add constraint removing all subsets of the current solution
constr_idx = [x for x in range(len(values)) if values[x] < 0.5]
constr = cplex.SparsePair(ind = constr_idx,
val = [1. for _ in constr_idx])
ilp.linear_constraints.add(lin_expr = [constr],
senses = ['G'], rhs = [1.])
ilp.solve()
return mutexes, set()