/**
* This method is the access point to the planning procedure. Initially, it adds all variables
* from axioms to the set of found vars, then does the linear planning. If lp does not solve the
* problem and there are subtasks, goal-driven recursive planning with backtracking is invoked.
* Planning is performed until no new variables are introduced into the algorithm.
*/
public EvaluationAlgorithm invokePlaning(Problem problem, boolean _computeAll) {
long startTime = System.currentTimeMillis();
computeAll = _computeAll;
EvaluationAlgorithm algorithm = new EvaluationAlgorithm();
PlanningContext context = problem.getCurrentContext();
// add all axioms at the beginning of an algorithm
Collection<Var> flattened = new HashSet<Var>();
for (Iterator<Rel> axiomIter = problem.getAxioms().iterator(); axiomIter.hasNext(); ) {
Rel rel = axiomIter.next();
unfoldVarsToSet(rel.getOutputs(), flattened);
// do not overwrite values of variables that come via args of compute() or as inputs of
// independent subtasks
if (!problem.getAssumptions().containsAll(flattened)
// do not overwrite values of already known variables.
// typically this is the case when a value of a variable
// is given in a scheme via a properties window
// && !problem.getKnownVars().containsAll( flattened )
) {
algorithm.addRel(rel);
}
axiomIter.remove();
context.getKnownVars().addAll(flattened);
flattened.clear();
}
context.getFoundVars().addAll(context.getKnownVars());
// remove all known vars with no relations
for (Iterator<Var> varIter = context.getKnownVars().iterator(); varIter.hasNext(); ) {
if (varIter.next().getRels().isEmpty()) {
varIter.remove();
}
}
// start planning
if (problem.getRelsWithSubtasks().isEmpty()
&& linearForwardSearch(context, algorithm, computeAll)) {
if (isLinearLoggingOn()) logger.debug("Problem solved without subtasks");
} else if (!problem.getRelsWithSubtasks().isEmpty() && subtaskPlanning(problem, algorithm)) {
if (isLinearLoggingOn()) logger.debug("Problem solved with subtasks");
} else if (!computeAll) {
if (isLinearLoggingOn()) logger.debug("Problem not solved");
}
if (!nested) {
logger.info("Planning time: " + (System.currentTimeMillis() - startTime) + "ms.");
}
return algorithm;
}
private boolean subtaskPlanning(Problem problem, EvaluationAlgorithm algorithm) {
if (isSubtaskLoggingOn())
logger.debug("!!!--------- Starting Planning With Subtasks ---------!!!");
final int maxDepthBackup = maxDepth;
if (isSubtaskLoggingOn())
logger.debug(
"maxDepthBackup:" + maxDepthBackup + " sbt: " + problem.getRelsWithSubtasks().size());
PlanningContext context = problem.getCurrentContext();
try {
Set<Rel> relsWithSubtasks = new LinkedHashSet<Rel>(problem.getRelsWithSubtasks());
if (isIncremental) {
int incrementalDepth = 0;
while (incrementalDepth
<= (isSubtaskRepetitionAllowed
? maxDepthBackup
: problem.getRelsWithSubtasks().size() - 1)) {
if (isSubtaskLoggingOn())
logger.debug(
"Incremental dfs, with max depth "
+ (incrementalDepth + 1)
+ " and "
+ problem.getRelsWithSubtasks().size()
+ " subtasks to solve");
maxDepth = incrementalDepth++;
// if we need to compute some specific goals, after reaching a certain depth, but not the
// maximal depth,
// the problem may be solved and there is no need to go any deeper.
if (subtaskPlanningImpl(context, relsWithSubtasks, algorithm, new LinkedList<Rel>(), 0)) {
if (isSubtaskLoggingOn())
logger.debug("The problem was solved during idfs after some intermediate MLB");
return true;
}
if (isSubtaskLoggingOn())
logger.debug("Unsolved subtask left: " + problem.getRelsWithSubtasks().size());
}
if (isSubtaskLoggingOn()) logger.debug("Fininshed incremental dfs");
} else {
if (!isSubtaskRepetitionAllowed) {
maxDepth = problem.getRelsWithSubtasks().size() - 1;
}
if (isSubtaskLoggingOn())
logger.debug("Starting subtask dfs with maxDepth: " + (maxDepth + 1));
if (subtaskPlanningImpl(context, relsWithSubtasks, algorithm, new LinkedList<Rel>(), 0)) {
if (isSubtaskLoggingOn())
logger.debug("The problem was solved during dfs after some intermediate MLB");
return true;
}
}
} finally {
if (isSubtaskLoggingOn()) logger.debug("Fininshed dfs");
maxDepth = maxDepthBackup;
indSubtasks.clear();
}
if (isSubtaskLoggingOn()) logger.debug("Invoking final linear planning");
return linearForwardSearch(context, algorithm, computeAll);
}