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public transform ( |
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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;
}
public void testAimaExample()
{
Sentence aimaEg = (Sentence)parser.parse("( B11 <=> (P12 OR P21))");
CNFTransformer transformer = new CNFTransformer();
Sentence transformed = transformer.transform(aimaEg);
List<Sentence> clauses = gatherer.getClausesFrom(transformed);
Sentence clause1 = (Sentence)parser.parse("( B11 OR ( NOT P12 ) )");
Sentence clause2 = (Sentence)parser.parse("( B11 OR ( NOT P21 ) )");
Sentence clause3 = (Sentence)parser
.parse("( ( NOT B11 ) OR ( P12 OR P21 ) )");
Assert.AreEqual(3, clauses.Count);
Assert.IsTrue(clauses.Contains(clause1));
Assert.IsTrue(clauses.Contains(clause2));
Assert.IsTrue(clauses.Contains(clause3));
}
