/// <summary>
/// Remplace chaque occurence d'une variable aléatoirement choisi par une constante, tel que la règle final correspond à un ou plusieurs états de l'environnement.
/// Echoue si une variable ne peut être remplacé en constante ou que la règle ne correspond à un ou plusieurs états.
/// </summary>
/// <param name="index">Index dans l'ensemble d'action.</param>
/// <param name="actionSet">Ensemble d'action à traiter.</param>
/// <param name="env">Environnement à prendre en compte.</param>
/// <returns>Le classifieur fils muté, null si la mutation échoue.</returns>
private Classifier VarToConst(int index, List <Classifier> actionSet, PerceivedEnvironnement env)
{
AppDomainSetup ads = new AppDomainSetup();
ads.ApplicationBase = AppDomain.CurrentDomain.BaseDirectory;
AppDomain appDomain = AppDomain.CreateDomain("PrologScript", null, ads);
string assembly = Assembly.GetEntryAssembly().FullName;
MatchMarshalRefByType mmrbt =
(MatchMarshalRefByType)appDomain.CreateInstanceAndUnwrap(assembly,
typeof(MatchMarshalRefByType).FullName);
List <HornClause> knowBase = fo.knowledgeBase.ToList();
var assertResult = mmrbt.AssertEnvironnement(env, knowBase, boundVarList, fo);
Dictionary <string, int> usedPredicate = assertResult.Value.Value;
Dictionary <Classifier, List <Attribute> > usedClassifiers = new Dictionary <Classifier, List <Attribute> >();
Dictionary <Attribute, List <HornClause> > accMatchSet = new Dictionary <Attribute, List <HornClause> >();
List <Classifier> matchSetCount = new List <Classifier>();
bool isMatching = false;
List <Classifier> actSet = ObjectCopier.Clone(actionSet);
Random rand = new Random();
Dictionary <ArgType, Dictionary <string, List <int[]> > > varList = GetAllValues(ArgMode.VAR, actionSet, index);
if (varList.Count != 0)
{
ArgType randArgType = varList.Keys.ToArray()[rand.Next(varList.Keys.Count)];;
string randVar = varList[randArgType].Keys.ToArray()[rand.Next(varList[randArgType].Count)];
if (varList[randArgType][randVar].Count != 0)
{
Attribute newHead = actSet[index].rule.head;
Attribute[] newBody = actSet[index].rule.body;
if (randArgType is ArgType.TOKEN)
{
foreach (string constVar in env.tokenOnBoard)
{
foreach (int[] argIndex in varList[randArgType][randVar])
{
if (argIndex[0] == -1)
{
if (newHead.predOp.argsOptions[argIndex[1]].argsMode.Contains(ArgMode.CONST))
{
newHead.values[argIndex[1]] = constVar;
}
}
else
{
if (newBody[argIndex[0]].predOp.argsOptions[argIndex[1]].argsMode.Contains(ArgMode.CONST))
{
newBody[argIndex[0]].values[argIndex[1]] = constVar;
}
}
}
Classifier newCl = new Classifier(currentTime, new HornClause(ObjectCopier.Clone(newHead), ObjectCopier.Clone(newBody)), fo);
string[] accValues = newHead.values.ToArray() as string[];
List <Attribute> actionMatchList = mmrbt.GetClassifierMatchList(newCl, env);
if (actionMatchList.Count != 0)
{
matchSetCount.Add(newCl);
}
}
}
else
{
foreach (string constVar in boundVarList[randArgType].Keys)
{
foreach (int[] argIndex in varList[randArgType][randVar])
{
if (argIndex[0] == -1)
{
if (newHead.predOp.argsOptions[argIndex[1]].argsMode.Contains(ArgMode.CONST))
{
newHead.values[argIndex[1]] = constVar;
}
}
else
{
if (newBody[argIndex[0]].predOp.argsOptions[argIndex[1]].argsMode.Contains(ArgMode.CONST))
{
newBody[argIndex[0]].values[argIndex[1]] = constVar;
}
}
}
Classifier newCl = new Classifier(currentTime, new HornClause(ObjectCopier.Clone(newHead), ObjectCopier.Clone(newBody)), fo);
string[] accValues = newHead.values.ToArray() as string[];
List <Attribute> actionMatchList = mmrbt.GetClassifierMatchList(newCl, env);
if (actionMatchList.Count != 0)
{
matchSetCount.Add(newCl);
}
}
}
mmrbt.AbolishEnvironnement(usedPredicate);
AppDomain.Unload(appDomain);
if (matchSetCount.Count != 0)
{
return(matchSetCount[rand.Next(matchSetCount.Count)]);
}
}
}
return(null);
}
/// <summary>
/// Ajoute un prédicat au corps de la règle et lui octroie des arguments aléatoires entres constantes, variables libres ou liées.
/// Si une constante est à ajouter, la règle finale doit correspondre à un ou plusieurs états de l'environnement.
/// </summary>
/// <param name="index">Index dans l'ensemble d'action.</param>
/// <param name="actionSet">Ensemble d'action à traiter.</param>
/// <param name="env">Environnement à prendre en compte.</param>
/// <returns>Le classifieur fils muté, null si la mutation échoue.</returns>
private Classifier AddAtom(int index, List <Classifier> actionSet, PerceivedEnvironnement env)
{
bool retry = false;
Attribute newHead = ObjectCopier.Clone(actionSet)[index].rule.head;
Attribute[] newBody = ObjectCopier.Clone(actionSet)[index].rule.body;
Classifier newCl = null;
List <string> availablePredicates = new List <string>();
foreach (Attribute state in env.states)
{
if (!availablePredicates.Contains(state.name))
{
availablePredicates.Add(state.name);
}
}
Random rand = new Random();
string randAtomName = availablePredicates[rand.Next(availablePredicates.Count)];
string[] randValues = new string[fo.statePredicateOptions[randAtomName].argsOptions.Count()];
Dictionary <int, List <string> > constList = new Dictionary <int, List <string> >();
int atomCount = 0;
foreach (Attribute predicate in actionSet[index].rule.body)
{
if (predicate.name.Equals(randAtomName))
{
atomCount++;
}
}
if (atomCount <= fo.statePredicateOptions[randAtomName].max && actionSet[index].rule.body.Length < fo.maxPredicate)
{
for (int i = 0; i < randValues.Count(); i++)
{
int accRand;
do
{
retry = false;
switch (fo.statePredicateOptions[randAtomName].argsOptions[i].argsMode[accRand = rand.Next(fo.statePredicateOptions[randAtomName].argsOptions[i].argsMode.Count())])
{
case ArgMode.CONST:
if (fo.statePredicateOptions[randAtomName].argsOptions[i].argType is ArgType.TOKEN)
{
if (!constList.ContainsKey(i))
{
constList.Add(i, env.tokenOnBoard);
}
}
else
{
if (!constList.ContainsKey(i))
{
constList.Add(i, boundVarList[fo.statePredicateOptions[randAtomName].argsOptions[i].argType].Keys.ToList());
}
}
break;
case ArgMode.VAR:
randValues[i] = fo.statePredicateOptions[randAtomName].argsOptions[i].argType.ToString() + varCount[fo.statePredicateOptions[randAtomName].argsOptions[i].argType];
varCount[fo.statePredicateOptions[randAtomName].argsOptions[i].argType]++;
break;
case ArgMode.BOUND:
Dictionary <ArgType, Dictionary <string, List <int[]> > > boundList = GetAllValues(ArgMode.BOUND, actionSet, index);
if (!boundList.ContainsKey(fo.statePredicateOptions[randAtomName].argsOptions[i].argType) ||
boundList[fo.statePredicateOptions[randAtomName].argsOptions[i].argType].Count == 0)
{
return(null);
}
string randBound = new List <string>(boundList[fo.statePredicateOptions[randAtomName].argsOptions[i].argType].Keys)[rand.Next(boundList[fo.statePredicateOptions[randAtomName].argsOptions[i].argType].Keys.Count)];
randValues[i] = randBound;
break;
default:
retry = true;
break;
}
} while (retry);
}
if (constList.Count != 0)
{
AppDomainSetup ads = new AppDomainSetup();
ads.ApplicationBase = AppDomain.CurrentDomain.BaseDirectory;
AppDomain appDomain = AppDomain.CreateDomain("PrologScript", null, ads);
string assembly = Assembly.GetEntryAssembly().FullName;
MatchMarshalRefByType mmrbt =
(MatchMarshalRefByType)appDomain.CreateInstanceAndUnwrap(assembly,
typeof(MatchMarshalRefByType).FullName);
List <HornClause> knowBase = fo.knowledgeBase.ToList();
var assertResult = mmrbt.AssertEnvironnement(env, knowBase, boundVarList, fo);
Dictionary <string, int> usedPredicate = assertResult.Value.Value;
Dictionary <Classifier, List <Attribute> > usedClassifiers = new Dictionary <Classifier, List <Attribute> >();
Dictionary <Attribute, List <HornClause> > accMatchSet = new Dictionary <Attribute, List <HornClause> >();
List <Classifier> matchSetCount = new List <Classifier>();
List <Attribute> accMatchList = new List <Attribute>();
Dictionary <int, int> accIterators = new Dictionary <int, int>();
foreach (int i in constList.Keys)
{
accIterators.Add(i, 0);
}
bool endIterators = false;
int accIndex = fo.statePredicateOptions[randAtomName].argsOptions.Count();
while (!endIterators)
{
newHead = ObjectCopier.Clone(actionSet)[index].rule.head;
newBody = ObjectCopier.Clone(actionSet)[index].rule.body;
foreach (int i in constList.Keys)
{
randValues[i] = constList[i][accIterators[i]];
}
var acc = ObjectCopier.Clone(newBody).ToList();
acc.Add(new Attribute(randAtomName, randValues.ToArray(), fo.statePredicateOptions[randAtomName]));
newBody = acc.ToArray();
newCl = new Classifier(currentTime, new HornClause(newHead, newBody.ToArray()), fo);
if ((accMatchList = mmrbt.GetClassifierMatchList(newCl, env)).Count != 0)
{
matchSetCount.Add(newCl);
}
for (int i = 0; i <= constList.Last().Key; i++)
{
if (constList.Keys.Contains(i))
{
accIterators[i]++;
while (i <= constList.Last().Key&& (!constList.Keys.Contains(i) || accIterators[i] >= constList[i].Count))
{
if (constList.Keys.Contains(i))
{
accIterators[i] = 0;
}
i++;
}
if (accIterators.Values.Sum() == 0 || accIterators[i] < constList[i].Count())
{
if (accIterators.Values.Sum() == 0)
{
endIterators = true;
}
break;
}
}
}
}
mmrbt.AbolishEnvironnement(usedPredicate);
AppDomain.Unload(appDomain);
if (matchSetCount.Count == 0)
{
return(null);
}
else
{
return(matchSetCount[rand.Next(matchSetCount.Count)]);
}
}
List <Attribute> predicateList = new List <Attribute>(actionSet[index].rule.body.ToArray());
predicateList.Add(new Attribute(randAtomName, randValues, fo.statePredicateOptions[randAtomName]));
Attribute[] newRule = predicateList.ToArray();
return(new Classifier(currentTime, new HornClause(actionSet[index].rule.head, newRule), fo));
}
return(null);
}
/// <summary>
/// Crée de nouveaux classifieurs dérivant de ceux présents dans l'ensemble d'action en appliquant des opérations de mutations.
/// Insère les nouveaux classifieurs dans la population et en supprime si la population est dépassée en terme de capacité.
/// Ne se lance que si le temps moyen écoulé depuis le dernier lancement de l'algorithme génétique sur l'ensemble des classifieurs de l'ensemble d'action est plus grand qu'une limite <see cref="FOXCSOptions.geneticThresh"/>.
/// </summary>
/// <param name="actionSet">Ensemble d'action à traiter.</param>
/// <param name="env">Environnement à utiliser.</param>
private void RunGeneticAlgorithm(List <Classifier> actionSet, PerceivedEnvironnement env)
{
int timeNumSum = 0;
int numSum = 0;
foreach (Classifier cl in actionSet)
{
timeNumSum += cl.timeStamp * cl.numerosity;
numSum += cl.numerosity;
}
if (numSum == 0)
{
return;
}
if (currentTime - timeNumSum / numSum > fo.geneticThresh)
{
Console.WriteLine("Executing Genetic Algorithm.");
Classifier newClassifier = null;
Random rand = new Random();
double prob = -1;
for (int i = 0; i < actionSet.Count; i++)
{
actionSet[i].timeStamp = currentTime;
while (newClassifier == null)
{
prob = rand.NextDouble();
if (fo.probMutationRange.mutRanges[0].InRange(prob))
{
newClassifier = DeleteAtom(i, actionSet, env);
}
else if (fo.probMutationRange.mutRanges[1].InRange(prob))
{
newClassifier = ConstToVar(i, actionSet, env);
}
else if (fo.probMutationRange.mutRanges[2].InRange(prob))
{
newClassifier = VarToAnonym(i, actionSet, env);
}
else if (fo.probMutationRange.mutRanges[3].InRange(prob))
{
newClassifier = AddAtom(i, actionSet, env);
}
else if (fo.probMutationRange.mutRanges[4].InRange(prob))
{
newClassifier = VarToConst(i, actionSet, env);
}
else if (fo.probMutationRange.mutRanges[5].InRange(prob))
{
newClassifier = AnonymToVar(i, actionSet, env);
}
else if (fo.probMutationRange.mutRanges[6].InRange(prob))
{
newClassifier = Reproduction(i, actionSet, env);
}
if (newClassifier != null)
{
int popIndex = ActionSetIndexOf(actionSet, newClassifier);
if (popIndex != -1)
{
actionSet[popIndex].numerosity++;
}
else
{
popIndex = PopSetIndexOf(newClassifier);
if (popIndex != -1)
{
popSet[popIndex].numerosity++;
}
else
{
popSet.Add(newClassifier);
}
}
DeleteFromPopulation();
}
}
}
}
}
private void DeleteFromPopulation()
{
int popSize = 0;
double fitnessSum = 0;
foreach (Classifier cl in popSet)
{
popSize += cl.numerosity;
fitnessSum += cl.fitness;
}
while (popSize > fo.popMaxSize)
{
double averageFitnessInPop = fitnessSum / popSize;
double voteSum = 0;
foreach (Classifier cl in popSet)
{
voteSum += DeletionVote(cl, averageFitnessInPop);
}
double choicePoint = new Random().NextDouble() * voteSum;
voteSum = 0;
for (int i = 0; i < popSet.Count; i++)
{
voteSum += DeletionVote(popSet[i], averageFitnessInPop);
if (voteSum > choicePoint)
{
if (popSet[i].numerosity > 1)
{
popSet[i].numerosity--;
}
else
{
Classifier accCl = popSet[i];
popSet.RemoveAt(i);
if (matchSet.Count != 0)
{
foreach (KeyValuePair <Attribute, List <Classifier> > matchSubSet in ObjectCopier.Clone(matchSet))
{
if (matchSubSet.Value.Contains(accCl))
{
matchSubSet.Value.RemoveAll(cl => cl.rule == accCl.rule);
if (matchSubSet.Value.Count == 0)
{
matchSet.Remove(matchSubSet.Key);
}
}
}
}
}
break;
}
popSize = 0;
fitnessSum = 0;
foreach (Classifier cl in popSet)
{
popSize += cl.numerosity;
fitnessSum += cl.fitness;
}
}
}
}
public YPMatchThread(ref Classifier cl, Attribute action)
{
this.cl = cl;
this.action = action;
this.clMatchList = new List <Attribute>();
}
/// <summary>
/// Méthode gérant la concordance d'un classifieur
/// </summary>
/// <param name="cl">Classifieur à vérifier.</param>
/// <param name="env">Environnement à insérer dans la base de prédicats.</param>
/// <param name="knowledgeBase">Clause constiuant la base de connaissance.</param>
/// <returns></returns>
public List <Attribute> GetClassifierMatchList(Classifier cl, PerceivedEnvironnement env)
{
List <Attribute> clMatchList = new List <Attribute>();
Dictionary <string, int> usedPredicate = new Dictionary <string, int>();
List <YPMatchThread> ypts = new List <YPMatchThread>();
List <Task> threads = new List <Task>();
foreach (Attribute action in env.actions)
{
if (cl.rule.head.name.Equals(action.name))
{
if (cl.rule.clause == null)
{
lock (_lock)
cl.rule.YPwriteAndCompile();
}
ypts.Insert(0, new YPMatchThread(ref cl, action));
threads.Insert(0, new Task(ypts[0].ActionMatch));
threads[0].Start();
}
/*
*
*
* if (cl.rule.head.name.Equals(action.name))
* {
* if (cl.rule.clause == null)
* lock (_lock)
* cl.rule.YPwriteAndCompile();
* foreach (bool l1 in cl.rule.Match(action.values))
* {
* clMatchList.Add(action);
* break;
* }
* }
*
*/
}
for (int j = 0; j < threads.Count; j++)
{
try
{
threads[j].Wait();
threads[j].Dispose();
}
catch (Exception e)
{
Console.WriteLine("Erreur provenant de YieldProlog, relancement du thread YPThread.");
Console.ReadKey();
Console.WriteLine(e);
threads[j].Dispose();
threads.Insert(0, new Task(ypts[j].ActionMatch));
}
}
foreach (YPMatchThread ypt in ypts)
{
foreach (Attribute actionMatch in ypt.clMatchList)
{
if (!clMatchList.Contains(actionMatch))
{
clMatchList.Add(actionMatch);
}
}
}
return(clMatchList);
}
