void model_test_3_aux(ai::PL::KnowledgeBase &kb,
std::vector<ai::PL::Symbol *> &symbols,
unsigned int pos)
{
kb.SetModel(symbols);
ai::PL::Symbol::State rval = kb.Evaluate();
if(rval == ai::PL::Symbol::KNOWN_TRUE)
{
std::cout << kb << std::endl;
std::cout << "Truth: " << rval << std::endl;
return;
}
else if(rval == ai::PL::Symbol::KNOWN_FALSE)
{
return;
}
// still unknown
count ++;
ai::PL::Symbol::State p;
for(p = ai::PL::Symbol::KNOWN_TRUE; p <= ai::PL::Symbol::KNOWN_FALSE; p++)
{
symbols[pos]->SetValue(p);
model_test_3_aux(kb, symbols, pos + 1);
}
}
int do_ask(ai::PL::KnowledgeBase &kb, int interactive, char *buf, std::istream &in, std::ostream &out, const char *prompt)
{
ai::PL::Symbol::State rval;
ai::PL::KnowledgeBase question;
char *q = 0;
unsigned int len = strlen(prompt);
if(strlen(buf) > len)
{
q = &buf[len];
}
else
{
if(interactive)
{
out << prompt << "> " << std::flush;
}
in.getline(buf, BUF_SIZE);
q = buf;
}
question.AddSentence(q);
if(!interactive)
{
out << prompt << " " << *(question.GetSentences()[0]) << std::endl;
}
if(strcmp(prompt, "dpll") == 0)
{
rval = kb.DPLL_Entails(question);
}
else if(strcmp(prompt, "ask2") == 0)
{
rval = kb.TT_Entails_Pruned(question);
}
else if(strcmp(prompt, "ask") == 0)
{
rval = kb.TT_Entails(question);
}
else
{
out << "Unknown ask mode: " << prompt << std::endl;
rval = ai::PL::Symbol::UNKNOWN;
}
if(rval == ai::PL::Symbol::KNOWN_TRUE)
{
out << "YES, " << q << " is entailed." << std::endl;
}
else
{
out << "NO, " << q << " is not entailed." << std::endl;
}
out << kb.GetCount() << " evaluations." << std::endl;
return 0;
}
int do_list(ai::PL::KnowledgeBase &kb, int interactive, char *buf, std::istream &in, std::ostream &out)
{
const std::vector<ai::PL::Sentence *> &sentences = kb.GetSentences();
std::vector<ai::PL::Sentence *>::const_iterator sen_it = sentences.begin();
while(sen_it != sentences.end())
{
out << *(*sen_it) << std::endl;
sen_it ++;
}
return 0;
}
void tt_entails_test_2_aux(ai::PL::KnowledgeBase &kb,
ai::PL::KnowledgeBase &alpha)
{
ai::PL::Symbol::State rval;
rval = kb.TT_Entails_Pruned(alpha);
std::cout << "KB" << std::endl << kb
<< "alpha" << std::endl << alpha
<< "result: " << rval
<< std::endl
<< std::endl;
}
int do_cnf(ai::PL::KnowledgeBase &kb, int interactive, char *buf, std::istream &in, std::ostream &out)
{
const std::vector<ai::PL::Sentence *> &sentences = kb.GetSentences();
std::vector<ai::PL::Sentence *>::const_iterator sen_it = sentences.begin();
while(sen_it != sentences.end())
{
ai::PL::Sentence *s_tmp = new ai::PL::Sentence(*(*sen_it));
s_tmp->CNF();
out << *(s_tmp) << std::endl;
sen_it ++;
delete s_tmp;
}
return 0;
}
int do_tell(ai::PL::KnowledgeBase &kb, int interactive, char *buf, std::istream &in, std::ostream &out)
{
char * sentence = 0;
if(strlen(buf) > 4)
{
sentence = &buf[4];
}
else
{
if(interactive)
{
out << "tell> " << std::flush;
}
in.getline(buf, BUF_SIZE);
sentence = buf;
}
kb.AddSentence(sentence);
if(!interactive)
{
out << "tell " << sentence << std::endl;
}
return 0;
}