// function SIMULATED-ANNEALING(problem, schedule) returns a solution state
// inputs: problem, a problem
// schedule, a mapping from time to "temperature"
public List<String> search(Problem p) throws Exception {
// local variables: current, a node
// next, a node
// T, a "temperature" controlling the probability of downward steps
clearInstrumentation();
outcome = SearchOutcome.FAILURE;
lastState = null;
// current <- MAKE-NODE(INITIAL-STATE[problem])
Node current = new Node(p.getInitialState());
Node next = null;
List<String> ret = new ArrayList<String>();
// for t <- 1 to INFINITY do
int timeStep = 0;
while (true) {
// temperature <- schedule[t]
double temperature = scheduler.getTemp(timeStep);
timeStep++;
// if temperature = 0 then return current
if (temperature == 0.0) {
if (p.isGoalState(current.getState())) {
outcome = SearchOutcome.SOLUTION_FOUND;
}
ret = SearchUtils.actionsFromNodes(current.getPathFromRoot());
lastState = current.getState();
break;
}
List<Node> children = expandNode(current, p);
if (children.size() > 0) {
// next <- a randomly selected successor of current
next = Util.selectRandomlyFromList(children);
// /\E <- VALUE[next] - VALUE[current]
int deltaE = getValue(p, next) - getValue(p, current);
if (shouldAccept(temperature, deltaE)) {
current = next;
}
}
}
return ret;
}
private int getHeuristic(Problem p, Node aNode) {
return p.getHeuristicFunction().getHeuristicValue(aNode.getState());
}
