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"""Returns a function that is True when x is equal to val, False otherwise"""
def isv(x):
return val == x
isv.__name__ = str(val) + "=="
return isv
def ne_(val):
"""Returns a function that is True when x is not equal to val, False otherwise"""
def nev(x):
return val != x
nev.__name__ = str(val) + "!="
return nev
def no_heuristic(to_do):
return to_do
def sat_up(to_do):
return SortedSet(to_do, key=lambda t: 1 / len([var for var in t[1].scope]))
class ACSolver:
"""Solves a CSP with arc consistency and domain splitting"""
def __init__(self, csp):
"""a CSP solver that uses arc consistency
* csp is the CSP to be solved
"""
self.csp = csp
def GAC(self, orig_domains=None, to_do=None, arc_heuristic=sat_up):
"""Makes this CSP arc-consistent using Generalized Arc Consistency
orig_domains is the original domains
to_do is a set of (variable,constraint) pairs
returns the reduced domains (an arc-consistent variable:domain dictionary)
"""
if orig_domains is None:
orig_domains = self.csp.domains
if to_do is None:
to_do = {(var, const) for const in self.csp.constraints for var in const.scope}
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else:
to_do = to_do.copy()
domains = orig_domains.copy()
to_do = arc_heuristic(to_do)
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while to_do:
var, const = to_do.pop()
other_vars = [ov for ov in const.scope if ov != var]
new_domain = set()
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if len(other_vars) == 0:
for val in domains[var]:
if const.holds({var: val}):
new_domain.add(val)
checks += 1
# new_domain = {val for val in domains[var]
# if const.holds({var: val})}
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elif len(other_vars) == 1:
other = other_vars[0]
for val in domains[var]:
for other_val in domains[other]:
checks += 1
if const.holds({var: val, other: other_val}):
new_domain.add(val)
break
# new_domain = {val for val in domains[var]
# if any(const.holds({var: val, other: other_val})
# for other_val in domains[other])}
else: # general case
for val in domains[var]:
holds, checks = self.any_holds(domains, const, {var: val}, other_vars, checks=checks)
if holds:
new_domain.add(val)
# new_domain = {val for val in domains[var]
# if self.any_holds(domains, const, {var: val}, other_vars)}
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if new_domain != domains[var]:
domains[var] = new_domain
if not new_domain:
return False, domains, checks
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add_to_do = self.new_to_do(var, const).difference(to_do)
to_do |= add_to_do
return True, domains, checks
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def new_to_do(self, var, const):
"""
Returns new elements to be added to to_do after assigning
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variable var in constraint const.
"""
return {(nvar, nconst) for nconst in self.csp.var_to_const[var]
if nconst != const
for nvar in nconst.scope
if nvar != var}
def any_holds(self, domains, const, env, other_vars, ind=0, checks=0):
"""
Returns True if Constraint const holds for an assignment
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that extends env with the variables in other_vars[ind:]
env is a dictionary
Warning: this has side effects and changes the elements of env
"""
if ind == len(other_vars):
return const.holds(env), checks + 1
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else:
var = other_vars[ind]
for val in domains[var]:
# env = dict_union(env, {var:val}) # no side effects
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env[var] = val
holds, checks = self.any_holds(domains, const, env, other_vars, ind + 1, checks)
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if holds:
return True, checks
return False, checks
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def domain_splitting(self, domains=None, to_do=None, arc_heuristic=sat_up):
"""
Return a solution to the current CSP or False if there are no solutions
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to_do is the list of arcs to check
"""
if domains is None:
domains = self.csp.domains
consistency, new_domains, _ = self.GAC(domains, to_do, arc_heuristic)
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if not consistency:
return False
elif all(len(new_domains[var]) == 1 for var in domains):
return {var: first(new_domains[var]) for var in domains}
else:
var = first(x for x in self.csp.variables if len(new_domains[x]) > 1)
if var:
dom1, dom2 = partition_domain(new_domains[var])
new_doms1 = extend(new_domains, var, dom1)
new_doms2 = extend(new_domains, var, dom2)
to_do = self.new_to_do(var, None)
return self.domain_splitting(new_doms1, to_do, arc_heuristic) or \
self.domain_splitting(new_doms2, to_do, arc_heuristic)
def partition_domain(dom):
"""partitions domain dom into two"""
split = len(dom) // 2
dom1 = set(list(dom)[:split])
dom2 = dom - dom1
return dom1, dom2
class ACSearchSolver(search.Problem):
"""A search problem with arc consistency and domain splitting
A node is a CSP"""
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def __init__(self, csp, arc_heuristic=sat_up):
self.cons = ACSolver(csp)
consistency, self.domains, _ = self.cons.GAC(arc_heuristic=arc_heuristic)
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if not consistency:
raise Exception('CSP is inconsistent')
self.heuristic = arc_heuristic
super().__init__(self.domains)
def goal_test(self, node):
"""node is a goal if all domains have 1 element"""
return all(len(node[var]) == 1 for var in node)
def actions(self, state):
var = first(x for x in state if len(state[x]) > 1)
neighs = []
if var:
dom1, dom2 = partition_domain(state[var])
to_do = self.cons.new_to_do(var, None)
for dom in [dom1, dom2]:
new_domains = extend(state, var, dom)
consistency, cons_doms, _ = self.cons.GAC(new_domains, to_do, self.heuristic)
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if consistency:
neighs.append(cons_doms)
return neighs
def result(self, state, action):
return action
def ac_solver(csp, arc_heuristic=sat_up):
"""arc consistency (domain splitting)"""
return ACSolver(csp).domain_splitting(arc_heuristic=arc_heuristic)
def ac_search_solver(csp, arc_heuristic=sat_up):
"""arc consistency (search interface)"""
from search import depth_first_tree_search
solution = None
try:
solution = depth_first_tree_search(ACSearchSolver(csp, arc_heuristic=arc_heuristic)).state
except:
return solution
if solution:
return {var: first(solution[var]) for var in solution}
# ______________________________________________________________________________
# Crossword Problem
csp_crossword = NaryCSP({'one_across': {'ant', 'big', 'bus', 'car', 'has'},
'one_down': {'book', 'buys', 'hold', 'lane', 'year'},
'two_down': {'ginger', 'search', 'symbol', 'syntax'},
'three_across': {'book', 'buys', 'hold', 'land', 'year'},
'four_across': {'ant', 'big', 'bus', 'car', 'has'}},
[Constraint(('one_across', 'one_down'), meet_at(0, 0)),
Constraint(('one_across', 'two_down'), meet_at(2, 0)),
Constraint(('three_across', 'two_down'), meet_at(2, 2)),
Constraint(('three_across', 'one_down'), meet_at(0, 2)),
Constraint(('four_across', 'two_down'), meet_at(0, 4))])
crossword1 = [['_', '_', '_', '*', '*'],
['_', '*', '_', '*', '*'],
['_', '_', '_', '_', '*'],
['_', '*', '_', '*', '*'],
['*', '*', '_', '_', '_'],
['*', '*', '_', '*', '*']]
words1 = {'ant', 'big', 'bus', 'car', 'has', 'book', 'buys', 'hold',
'lane', 'year', 'ginger', 'search', 'symbol', 'syntax'}
class Crossword(NaryCSP):
def __init__(self, puzzle, words):
domains = {}
constraints = []
for i, line in enumerate(puzzle):
scope = []
for j, element in enumerate(line):
if element == '_':
var = "p" + str(j) + str(i)
domains[var] = list(string.ascii_lowercase)
scope.append(var)
else:
if len(scope) > 1:
constraints.append(Constraint(tuple(scope), is_word(words)))
scope.clear()
if len(scope) > 1:
constraints.append(Constraint(tuple(scope), is_word(words)))
puzzle_t = list(map(list, zip(*puzzle)))
for i, line in enumerate(puzzle_t):
scope = []
for j, element in enumerate(line):
if element == '_':
scope.append("p" + str(i) + str(j))
else:
if len(scope) > 1:
constraints.append(Constraint(tuple(scope), is_word(words)))
scope.clear()
if len(scope) > 1:
constraints.append(Constraint(tuple(scope), is_word(words)))
super().__init__(domains, constraints)
self.puzzle = puzzle
def display(self, assignment=None):
for i, line in enumerate(self.puzzle):
puzzle = ""
for j, element in enumerate(line):
if element == '*':
puzzle += "[*] "
else:
var = "p" + str(j) + str(i)
if assignment is not None:
if isinstance(assignment[var], set) and len(assignment[var]) is 1:
puzzle += "[" + str(first(assignment[var])).upper() + "] "
elif isinstance(assignment[var], str):
puzzle += "[" + str(assignment[var]).upper() + "] "
else:
puzzle += "[_] "
else:
puzzle += "[_] "
print(puzzle)
# ______________________________________________________________________________
Donato Meoli
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# Kakuro Problem
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# difficulty 0
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kakuro1 = [['*', '*', '*', [6, ''], [3, '']],
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['*', [4, ''], [3, 3], '_', '_'],
[['', 10], '_', '_', '_', '_'],
[['', 3], '_', '_', '*', '*']]
# difficulty 0
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kakuro2 = [
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['*', [10, ''], [13, ''], '*'],
[['', 3], '_', '_', [13, '']],
[['', 12], '_', '_', '_'],
[['', 21], '_', '_', '_']]
# difficulty 1
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kakuro3 = [
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['*', [17, ''], [28, ''], '*', [42, ''], [22, '']],
[['', 9], '_', '_', [31, 14], '_', '_'],
[['', 20], '_', '_', '_', '_', '_'],
['*', ['', 30], '_', '_', '_', '_'],
['*', [22, 24], '_', '_', '_', '*'],
[['', 25], '_', '_', '_', '_', [11, '']],
[['', 20], '_', '_', '_', '_', '_'],
[['', 14], '_', '_', ['', 17], '_', '_']]
# difficulty 2
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kakuro4 = [
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['*', '*', '*', '*', '*', [4, ''], [24, ''], [11, ''], '*', '*', '*', [11, ''], [17, ''], '*', '*'],
['*', '*', '*', [17, ''], [11, 12], '_', '_', '_', '*', '*', [24, 10], '_', '_', [11, ''], '*'],
['*', [4, ''], [16, 26], '_', '_', '_', '_', '_', '*', ['', 20], '_', '_', '_', '_', [16, '']],
[['', 20], '_', '_', '_', '_', [24, 13], '_', '_', [16, ''], ['', 12], '_', '_', [23, 10], '_', '_'],
[['', 10], '_', '_', [24, 12], '_', '_', [16, 5], '_', '_', [16, 30], '_', '_', '_', '_', '_'],
['*', '*', [3, 26], '_', '_', '_', '_', ['', 12], '_', '_', [4, ''], [16, 14], '_', '_', '*'],
['*', ['', 8], '_', '_', ['', 15], '_', '_', [34, 26], '_', '_', '_', '_', '_', '*', '*'],
['*', ['', 11], '_', '_', [3, ''], [17, ''], ['', 14], '_', '_', ['', 8], '_', '_', [7, ''], [17, ''], '*'],
['*', '*', '*', [23, 10], '_', '_', [3, 9], '_', '_', [4, ''], [23, ''], ['', 13], '_', '_', '*'],
['*', '*', [10, 26], '_', '_', '_', '_', '_', ['', 7], '_', '_', [30, 9], '_', '_', '*'],
['*', [17, 11], '_', '_', [11, ''], [24, 8], '_', '_', [11, 21], '_', '_', '_', '_', [16, ''], [17, '']],
[['', 29], '_', '_', '_', '_', '_', ['', 7], '_', '_', [23, 14], '_', '_', [3, 17], '_', '_'],
[['', 10], '_', '_', [3, 10], '_', '_', '*', ['', 8], '_', '_', [4, 25], '_', '_', '_', '_'],
['*', ['', 16], '_', '_', '_', '_', '*', ['', 23], '_', '_', '_', '_', '_', '*', '*'],
['*', '*', ['', 6], '_', '_', '*', '*', ['', 15], '_', '_', '_', '*', '*', '*', '*']]
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class Kakuro(NaryCSP):
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def __init__(self, puzzle):
variables = []
for i, line in enumerate(puzzle):
# print line
for j, element in enumerate(line):
if element == '_':
var1 = str(i)
if len(var1) == 1:
var1 = "0" + var1
var2 = str(j)
if len(var2) == 1:
var2 = "0" + var2
variables.append("X" + var1 + var2)
domains = {}
for var in variables:
domains[var] = set(range(1, 10))
constraints = []
for i, line in enumerate(puzzle):
for j, element in enumerate(line):
if element != '_' and element != '*':
# down - column
if element[0] != '':
x = []
for k in range(i + 1, len(puzzle)):
if puzzle[k][j] != '_':
break
var1 = str(k)
if len(var1) == 1:
var1 = "0" + var1
var2 = str(j)
if len(var2) == 1:
var2 = "0" + var2
x.append("X" + var1 + var2)
constraints.append(Constraint(x, sum_(element[0])))
constraints.append(Constraint(x, all_diff))
# right - line
if element[1] != '':
x = []
for k in range(j + 1, len(puzzle[i])):
if puzzle[i][k] != '_':
break
var1 = str(i)
if len(var1) == 1:
var1 = "0" + var1
var2 = str(k)
if len(var2) == 1:
var2 = "0" + var2
x.append("X" + var1 + var2)
constraints.append(Constraint(x, sum_(element[1])))
constraints.append(Constraint(x, all_diff))
super().__init__(domains, constraints)
self.puzzle = puzzle
def display(self, assignment=None):
for i, line in enumerate(self.puzzle):
puzzle = ""
for j, element in enumerate(line):
if element == '*':
puzzle += "[*]\t"
elif element == '_':
var1 = str(i)
if len(var1) == 1:
var1 = "0" + var1
var2 = str(j)
if len(var2) == 1:
var2 = "0" + var2
var = "X" + var1 + var2
if assignment is not None:
if isinstance(assignment[var], set) and len(assignment[var]) is 1:
puzzle += "[" + str(first(assignment[var])) + "]\t"
elif isinstance(assignment[var], int):
puzzle += "[" + str(assignment[var]) + "]\t"
else:
puzzle += "[_]\t"
else:
puzzle += "[_]\t"
else:
puzzle += str(element[0]) + "\\" + str(element[1]) + "\t"
print(puzzle)
# ______________________________________________________________________________
# Cryptarithmetic Problem
# [Figure 6.2]
# T W O + T W O = F O U R
two_two_four = NaryCSP({'T': set(range(1, 10)), 'F': set(range(1, 10)),
'W': set(range(0, 10)), 'O': set(range(0, 10)), 'U': set(range(0, 10)), 'R': set(range(0, 10)),
'C1': set(range(0, 2)), 'C2': set(range(0, 2)), 'C3': set(range(0, 2))},
[Constraint(('T', 'F', 'W', 'O', 'U', 'R'), all_diff),
Constraint(('O', 'R', 'C1'), lambda o, r, c1: o + o == r + 10 * c1),
Constraint(('W', 'U', 'C1', 'C2'), lambda w, u, c1, c2: c1 + w + w == u + 10 * c2),
Constraint(('T', 'O', 'C2', 'C3'), lambda t, o, c2, c3: c2 + t + t == o + 10 * c3),
Constraint(('F', 'C3'), eq)])
# S E N D + M O R E = M O N E Y
send_more_money = NaryCSP({'S': set(range(1, 10)), 'M': set(range(1, 10)),
'E': set(range(0, 10)), 'N': set(range(0, 10)), 'D': set(range(0, 10)),
'O': set(range(0, 10)), 'R': set(range(0, 10)), 'Y': set(range(0, 10)),
'C1': set(range(0, 2)), 'C2': set(range(0, 2)), 'C3': set(range(0, 2)),
'C4': set(range(0, 2))},
[Constraint(('S', 'E', 'N', 'D', 'M', 'O', 'R', 'Y'), all_diff),
Constraint(('D', 'E', 'Y', 'C1'), lambda d, e, y, c1: d + e == y + 10 * c1),
Constraint(('N', 'R', 'E', 'C1', 'C2'), lambda n, r, e, c1, c2: c1 + n + r == e + 10 * c2),
Constraint(('E', 'O', 'N', 'C2', 'C3'), lambda e, o, n, c2, c3: c2 + e + o == n + 10 * c3),
Constraint(('S', 'M', 'O', 'C3', 'C4'), lambda s, m, o, c3, c4: c3 + s + m == o + 10 * c4),
Constraint(('M', 'C4'), eq)])