C# (CSharp) AIMA.Core.Logic.Propositional.Algorithms Model.flip Examples

flip() public method

public flip ( Symbol s ) : Model
s	AIMA.Core.Logic.Propositional.Parsing.Ast.Symbol
return	Model

Example #1

File: WalkSAT.cs Project: PaulMineau/AIMA.Net

        private Symbol getSymbolWhoseFlipMaximisesSatisfiedClauses(
                List<Sentence> clauses, List<Symbol> symbols, Model model)
        {
            if (symbols.Count > 0)
            {
                Symbol retVal = symbols[0];
                int maxClausesSatisfied = 0;
                for (int i = 0; i < symbols.Count; i++)
                {
                    Symbol sym = symbols[i];
                    if (getNumberOfClausesSatisfiedIn(clauses, model.flip(sym)) > maxClausesSatisfied)
                    {
                        retVal = sym;
                        maxClausesSatisfied = getNumberOfClausesSatisfiedIn(
                                clauses, model.flip(sym));
                    }
                }
                return retVal;
            }
            else
            {
                return null;
            }

        }

Example #2

 private Symbol getSymbolWhoseFlipMaximisesSatisfiedClauses(
     List <Sentence> clauses, List <Symbol> symbols, Model model)
 {
     if (symbols.Count > 0)
     {
         Symbol retVal = symbols[0];
         int    maxClausesSatisfied = 0;
         for (int i = 0; i < symbols.Count; i++)
         {
             Symbol sym = symbols[i];
             if (getNumberOfClausesSatisfiedIn(clauses, model.flip(sym)) > maxClausesSatisfied)
             {
                 retVal = sym;
                 maxClausesSatisfied = getNumberOfClausesSatisfiedIn(
                     clauses, model.flip(sym));
             }
         }
         return(retVal);
     }
     else
     {
         return(null);
     }
 }

Example #3

        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);
        }

Example #4

File: WalkSAT.cs Project: PaulMineau/AIMA.Net

        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;
        }