def read_environment(filename):
global env, state, time, readBefore
f = open(filename, 'r')
line = f.readline()
values = line.split()
X = int(values[0])
T = int(values[1])
S = int(values[2])
C = int(values[3])
M = int(values[4])
N = int(values[5])
P = int(values[6])
crtIndex = int(values[7])
time = int(T)
if readBefore:
for a in state:
if a[0] == 'location':
state.remove(a)
break
state.append(make_atom('location', make_const(crtIndex)))
if not readBefore:
env['capacity'].append(make_atom('capacity', make_const(C)))
for i in range(S):
state.append(make_atom('carries', make_const(i), make_const(C)))
line = f.readline()
if not readBefore:
values = line.split()
for i in values:
env['isWarehouse'].append(make_atom('isWarehouse', make_const(int(i))))
for i in range(int(P)):
line = f.readline()
if not readBefore:
values = line.split()
env['edge'].append(make_atom('edge', make_const(int(values[0])), make_const(int(values[1])), make_const(int(values[2]))))
env['edge'].append(make_atom('edge', make_const(int(values[1])), make_const(int(values[0])), make_const(int(values[2]))))
env['isDirty'] = []
for i in range(int(N)):
line = f.readline()
values = line.split()
index = int(values[0])
dirty = int(values[1])
dim = int(values[2])
nr_subst = int(values[3])
if not readBefore:
env['isRoom'].append(make_atom('isRoom', make_const(index)))
env['dimension'].append(make_atom('dimension', make_const(index), make_const(dim)))
if dirty == 1:
env['isDirty'].append(make_atom('isDirty', make_const(index)))
for j in range(4, 4 + 2 * nr_subst, 2):
env['substance'].append(make_atom('substance', make_const(index), make_const(int(values[j])), make_const(int(values[j+1]))))
readBefore = True
def get_sports_kb():
sports_kb = []
# Predicatul 'Consecutive'
add_statement(sports_kb, make_atom('Consecutive', make_const('Luni'), make_const('Marti')))
add_statement(sports_kb, make_atom('Consecutive', make_const('Marti'), make_const('Miercuri')))
add_statement(sports_kb, make_atom('Consecutive', make_const('Miercuri'), make_const('Joi')))
add_statement(sports_kb, make_atom('Consecutive', make_const('Joi'), make_const('Vineri')))
add_statement(sports_kb, make_atom('Consecutive', make_const('Vineri'), make_const('Sambata')))
add_statement(sports_kb, make_atom('Consecutive', make_const('Sambata'), make_const('Duminica')))
# Predicatul 'Weekend'
add_statement(sports_kb, make_atom('Weekend', make_const('Sambata')))
add_statement(sports_kb, make_atom('Weekend', make_const('Duminica')))
# Predicatul 'Ploua'
add_statement(sports_kb, make_atom('Ploua', make_const('Vineri')))
# TODO 2.1: Dacă a plouat două zile la rând, a treia zi va fi frumos.
add_statement(sports_kb, make_atom('Frumos', make_var('day3')), make_atom('Ploua', make_var('day1')),
make_atom('Ploua', make_var('day2')), make_atom('Consecutive', make_var('day1'), make_var('day2')),
make_atom('Consecutive', make_var('day2'), make_var('day3')))
# Predicatul 'Frumos'
add_statement(sports_kb, make_atom('Frumos', make_const('Luni')))
add_statement(sports_kb, make_atom('Frumos', make_const('Marti')))
add_statement(sports_kb, make_atom('Frumos', make_const('Miercuri')))
# TODO 2.2: Dacă a fost frumos trei zile la rând, în cea de-a patra zi va ploua.
add_statement(sports_kb, make_atom('Ploua', make_var('day4')), make_atom('Frumos', make_var('day1')),
make_atom('Frumos', make_var('day2')), make_atom('Frumos', make_var('day3')),
make_atom('Consecutive', make_var('day1'), make_var('day2')), make_atom('Consecutive', make_var('day2'), make_var('day3')),
make_atom('Consecutive', make_var('day3'), make_var('day4')))
# Predicatul 'Student'
add_statement(sports_kb, make_atom('Student', make_const('Nectarie')))
add_statement(sports_kb, make_atom('Student', make_const('Arsenie')))
# MergeLaMunte (cine, cand)
# TODO 2.3: Un student merge întotdeauna la munte dacă este frumos într-o zi de weekend.
add_statement(sports_kb, make_atom('MergeLaMunte', make_var('Student'), make_var('when')), make_atom('Weekend', make_var('when')),
make_atom('Frumos', make_var('when')))
# Predicatul 'SportDeVara'
add_statement(sports_kb, make_atom('SportDeVara', make_const('Volei')))
# Predicatul 'SportDeIarna'
add_statement(sports_kb, make_atom('SportDeIarna', make_const('Schi')))
add_statement(sports_kb, make_atom('SportDeIarna', make_const('Sanie')))
# Predicatul 'PracticaSport'
add_statement(sports_kb, make_atom('PracticaSport', make_const('Nectarie'), make_const('Schi')))
add_statement(sports_kb, make_atom('PracticaSport', make_const('Nectarie'), make_const('Sanie')))
add_statement(sports_kb, make_atom('PracticaSport', make_const('Arsenie'), make_const('Schi')))
add_statement(sports_kb, make_atom('PracticaSport', make_const('Arsenie'), make_const('Volei')))
# Predicatul 'Activitate'
add_statement(sports_kb, make_atom('Activitate', make_var('who'), make_var('what'), make_var('when')),
make_atom('MergeLaMunte', make_var('who'), make_var('when')),
make_atom('PracticaSport', make_var('who'), make_var('what')))
make_unique_var_names(sports_kb)
return sports_kb
for arg in get_args(formula):
if is_positive_literal(arg):
return arg
def is_fact(formula):
return is_positive_literal(formula)
def is_rule(formula):
return get_head(formula) == 'or' or get_head(formula) == 'and'
# Test!
# formula: P(x) ^ Q(x) -> R(x)
f = make_or(make_neg(make_atom("P", make_var("x"))),
make_neg(make_atom("Q", make_var("x"))),
make_atom("R", make_var("x")))
print(" ; ".join([print_formula(p, True)
for p in get_premises(f)])) # Should be P(?x) ; Q(?x)
print_formula(get_conclusion(f)) # Should be R(?x)
print(is_rule(f)) # must be True
print(is_fact(f)) # must be False
print(is_fact(get_conclusion(f))) # must be True
print(is_rule(get_conclusion(f))) # must be False
def equal_terms(t1, t2):
if is_constant(t1) and is_constant(t2):
return get_value(t1) == get_value(t2)
if is_variable(t1) and is_variable(t2):
'edge': [],
'isRoom': [],
'isWarehouse': [],
'capacity': []
}
math_predicates = ['isBigger', 'isSmaller', 'equal', 'sum', 'dif']
state = []
newState = []
reward = 0
time = -1
readBefore = False
# (action_name, [preconditions], [repetitive preconditions], [LA], [LE])
actions = [
('Move', [make_var('r1'), make_var('r2')],
[make_atom('location', make_var('r1')), make_atom('edge', make_var('r1'), make_var('r2'), make_var('cost'))],
[],
[make_atom('location', make_var('r2'))],
[make_atom('location', make_var('r1'))]),
('Clean', [make_var('r')],
[make_atom('location', make_var('r')), make_atom('isRoom', make_var('r')),
make_atom('isDirty', make_var('r')), make_atom('dimension', make_var('r'), make_var('dim'))],
[make_atom('substance', make_var('r'), make_var('s'), make_var('n')),
make_atom('carries', make_var('s'), make_var('m')), make_atom('isBigger', make_var('m'), make_var('n')),
make_atom('dif', make_var('m'), make_var('n'), make_var('d'))],
[make_atom('carries', make_var('s'), make_var('d'))],
[make_atom('isDirty', make_var('r')), make_atom('carries', make_var('s'), make_var('m'))]),
('Refill', [make_var('w')],
[make_atom('location', make_var('w')), make_atom('isWarehouse', make_var('w')),
make_atom('capacity', make_var('n')), make_atom('carries', make_var('sprim'), make_var('mprim')),
make_atom('isSmaller', make_var('mprim'), make_var('n'))],
def findBestAction(availableActions, path):
# TODO
global state, time
cost = 0
if 'Clean' in availableActions.keys():
cost = get_value(availableActions['Clean'][0][0]['dim'])
return ['Clean', 0, cost, cost]
if 'Refill' in availableActions.keys():
return ['Refill', 0, 1, 0]
if 'Move' in availableActions.keys():
substIndex = 0
maxReward = -1
cost = -1
for subst in availableActions['Move']:
moveCost = get_value(subst[0]['cost'])
print('move cost ' + str(moveCost) + " time " + str(time))
if moveCost > time:
continue
index = availableActions['Move'].index(subst)
if len(path) >= 1 and getActionName(path[len(path) - 1]) == 'Move':
args = getActionArgs(path[-1])
#print("ARGS " + str(args))
if int(args[0]) == get_value(
subst[0]['r2']) and len(availableActions['Move']) > 1:
continue
#TODO apply action
# nu merge applyaction pentru ca ar modifica si env; asa schimb manual doar locatia
#newState = applyAction(actions[0], subst)
newState = deepcopy(state)
for atom in newState:
if get_head(atom) == 'location':
newState.remove(atom)
break
newState.append(
make_atom('location', make_const(get_value(subst[0]['r2']))))
#TODO see available actions for the new states
newAvailableActions = findAvailableActions(newState)
print(newAvailableActions.keys())
#TODO pick the best move
if 'Clean' in newAvailableActions:
cleanCost = get_value(
newAvailableActions['Clean'][0][0]['dim'])
print("Clean cost " + str(cleanCost) + " max reward so far " +
str(maxReward))
if 1000 + cleanCost - moveCost > maxReward and moveCost + cleanCost <= time:
maxReward = 1000 + cleanCost - moveCost
substIndex = index
cost = moveCost
if 'Refill' in newAvailableActions:
print("Refill" + " max reward so far " + str(maxReward))
if 50 - moveCost > maxReward:
maxReward = 50 - moveCost
substIndex = index
cost = moveCost
# if 'Move' in newAvailableActions and len(newAvailableActions['Move']) > 1: # daca nu e dead end
# if 0 > maxReward:
# maxReward = 0
# substIndex = index
# cost = moveCost
print("chosen cost " + str(cost))
if cost != -1:
return ['Move', substIndex, cost, 0]
else:
substIndex = 0
minCost = 9999
for subst in availableActions['Move']:
moveCost = get_value(subst[0]['cost'])
if moveCost > time:
continue
index = availableActions['Move'].index(subst)
if len(path) >= 1 and getActionName(
path[len(path) - 1]) == 'Move':
args = getActionArgs(path[-1])
#print("ARGS " + str(args))
if int(args[0]) == get_value(subst[0]['r2']) and len(
availableActions['Move']) > 1:
continue
if moveCost < minCost:
substIndex = index
minCost = moveCost
print("new chosen cost " + str(minCost))
return ['Move', substIndex, minCost, 0]
return [None, None, 0, 0]