|
public getSymbolsIn ( |
||
| s | ||
| return | List |
|
public bool ttEntails(KnowledgeBase kb, String alpha)
{
Sentence kbSentence = kb.asSentence();
Sentence querySentence = (Sentence)new PEParser().parse(alpha);
SymbolCollector collector = new SymbolCollector();
List<Symbol> kbSymbols = collector.getSymbolsIn(kbSentence);
List<Symbol> querySymbols = collector.getSymbolsIn(querySentence);
List<Symbol> symbols = SetOps.union(kbSymbols, querySymbols);
List<Symbol> symbolList = symbols;
return ttCheckAll(kbSentence, querySentence, symbolList, new Model());
}
public Model findModelFor(String logicalSentence, int numberOfFlips,
double probabilityOfRandomWalk)
{
myModel = new Model();
Sentence s = (Sentence)new PEParser().parse(logicalSentence);
CNFTransformer transformer = new CNFTransformer();
CNFClauseGatherer clauseGatherer = new CNFClauseGatherer();
SymbolCollector sc = new SymbolCollector();
List<Symbol> symbols = sc.getSymbolsIn(s);
Random r = new Random();
for (int i = 0; i < symbols.Count; i++)
{
Symbol sym = (Symbol)symbols[i];
myModel = myModel.extend(sym, Util.randombool());
}
List<Sentence> clauses = clauseGatherer.getClausesFrom(transformer
.transform(s));
for (int i = 0; i < numberOfFlips; i++)
{
if (getNumberOfClausesSatisfiedIn(clauses, myModel) == clauses.Count)
{
return myModel;
}
Sentence clause = clauses[random.Next(clauses.Count)];
List<Symbol> symbolsInClause = sc
.getSymbolsIn(clause);
if (random.NextDouble() >= probabilityOfRandomWalk)
{
Symbol randomSymbol = symbolsInClause[random
.Next(symbolsInClause.Count)];
myModel = myModel.flip(randomSymbol);
}
else
{
Symbol symbolToFlip = getSymbolWhoseFlipMaximisesSatisfiedClauses(
clauses,
symbolsInClause, myModel);
myModel = myModel.flip(symbolToFlip);
}
}
return null;
}