class BackwardInferenceAgent(MindAgent):
def __init__(self):
self.chainer = None
def create_chainer(self, atomspace):
self.chainer = Chainer(atomspace, stimulateAtoms=False, agent=self)
deduction_link_types = [types.InheritanceLink]
# types.SubsetLink, types.IntensionalInheritanceLink]
for link_type in deduction_link_types:
self.chainer.add_rule(rules.InversionRule(self.chainer, link_type))
self.chainer.add_rule(rules.DeductionRule(self.chainer, link_type))
# self.chainer.add_rule(rules.NotCreationRule(self.chainer))
# self.chainer.add_rule(rules.NotEliminationRule(self.chainer))
# for rule in rules.create_and_or_rules(self.chainer, 1, 5):
# self.chainer.add_rule(rule)
# self.chainer.add_rule(EvaluationToMemberRule(self.chainer))
# self.chainer.add_rule(MemberToInheritanceRule(self.chainer))
def run(self, atomspace):
# incredibly exciting futuristic display!
#import os
#os.system('cls' if os.name=='nt' else 'clear')
# try:
if self.chainer is None:
self.create_chainer(atomspace)
result = self.chainer.backward_step()
if result:
(outputs, inputs) = result
if False:
print '==== Inference ===='
print show_atoms(outputs), '<=', show_atoms(inputs)
print
print '==== Attentional Focus ===='
for atom in get_attentional_focus(atomspace)[0:30]:
print str(atom), atom.av
#print '==== Result ===='
#print output
#print '==== Trail ===='
#print_atoms( self.chainer.trails[output] )
if self.chainer._all_nonzero_tvs(inputs):
raw_input()
else:
print 'Invalid inference attempted'
class BackwardInferenceAgent(MindAgent):
def __init__(self):
self.chainer = None
def create_chainer(self, atomspace):
self.chainer = Chainer(atomspace, stimulateAtoms = False, agent = self)
deduction_link_types = [types.InheritanceLink]
# types.SubsetLink, types.IntensionalInheritanceLink]
for link_type in deduction_link_types:
self.chainer.add_rule(rules.InversionRule(self.chainer, link_type))
self.chainer.add_rule(rules.DeductionRule(self.chainer, link_type))
# self.chainer.add_rule(rules.NotCreationRule(self.chainer))
# self.chainer.add_rule(rules.NotEliminationRule(self.chainer))
# for rule in rules.create_and_or_rules(self.chainer, 1, 5):
# self.chainer.add_rule(rule)
# self.chainer.add_rule(EvaluationToMemberRule(self.chainer))
# self.chainer.add_rule(MemberToInheritanceRule(self.chainer))
def run(self, atomspace):
# incredibly exciting futuristic display!
#import os
#os.system('cls' if os.name=='nt' else 'clear')
# try:
if self.chainer is None:
self.create_chainer(atomspace)
result = self.chainer.backward_step()
if result:
(outputs, inputs) = result
if False:
print '==== Inference ===='
print show_atoms(outputs), '<=', show_atoms(inputs)
print
print '==== Attentional Focus ===='
for atom in get_attentional_focus(atomspace)[0:30]:
print str(atom), atom.av
#print '==== Result ===='
#print output
#print '==== Trail ===='
#print_atoms( self.chainer.trails[output] )
if self.chainer._all_nonzero_tvs(inputs):
raw_input()
else:
print 'Invalid inference attempted'
