public getSymbolsIn ( |
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리턴 | 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; }