// function HILL-CLIMBING(problem) returns a state that is a local maximum
public List<Action> search(Problem p) {
clearInstrumentation();
outcome = SearchOutcome.FAILURE;
lastState = null;
// current <- MAKE-NODE(problem.INITIAL-STATE)
Node current = new Node(p.getInitialState());
Node neighbor = null;
// loop do
while (!CancelableThread.currIsCanceled()) {
List<Node> children = expandNode(current, p);
// neighbor <- a highest-valued successor of current
neighbor = getHighestValuedNodeFrom(children, p);
// if neighbor.VALUE <= current.VALUE then return current.STATE
if ((neighbor == null) || (getValue(neighbor) <= getValue(current))) {
if (SearchUtils.isGoalState(p, current)) {
outcome = SearchOutcome.SOLUTION_FOUND;
}
lastState = current.getState();
return SearchUtils.actionsFromNodes(current.getPathFromRoot());
}
// current <- neighbor
current = neighbor;
}
return new List<Action>();
}
// function DEPTH-LIMITED-SEARCH(problem, limit) returns a solution, or
// failure/cutoff
/**
* @param p
* @return if goal found, the list of actions to the Goal. If already at the
* goal you will receive a List with a single NoOp Action in it. If
* fail to find the Goal, an empty list will be returned to indicate
* that the search failed. If the search was cutoff (i.e. reached
* its limit without finding a goal) a List with one
* CutOffIndicatorAction.CUT_OFF in it will be returned (Note: this
* is a NoOp action).
*/
public List<Action> search(Problem p)
{
clearInstrumentation();
// return RECURSIVE-DLS(MAKE-NODE(INITIAL-STATE[problem]), problem,
// limit)
return recursiveDLS(new Node(p.getInitialState()), p, limit);
}
/**
*
* @param problem
* @param frontier
* @return if goal found, the list of actions to the Goal. If already at the
* goal you will receive a List with a single NoOp Action in it. If
* fail to find the Goal, an empty list will be returned to indicate
* that the search failed.
*/
public virtual List <Action> search(Problem problem, Queue <Node> frontier)
{
this.frontier = frontier;
clearInstrumentation();
// initialize the frontier using the initial state of the problem
Node root = new Node(problem.getInitialState());
if (isCheckGoalBeforeAddingToFrontier())
{
if (SearchUtils.isGoalState(problem, root))
{
return(SearchUtils.actionsFromNodes(root.getPathFromRoot()));
}
}
frontier.Enqueue(root);
setQueueSize(frontier.Count);
while (!(frontier.Count == 0))
{
// choose a leaf node and remove it from the frontier
Node nodeToExpand = popNodeFromFrontier();
setQueueSize(frontier.Count);
// Only need to check the nodeToExpand if have not already
// checked before adding to the frontier
if (!isCheckGoalBeforeAddingToFrontier())
{
// if the node contains a goal state then return the
// corresponding solution
if (SearchUtils.isGoalState(problem, nodeToExpand))
{
setPathCost(nodeToExpand.getPathCost());
return(SearchUtils.actionsFromNodes(nodeToExpand
.getPathFromRoot()));
}
}
// expand the chosen node, adding the resulting nodes to the
// frontier
foreach (Node fn in getResultingNodesToAddToFrontier(nodeToExpand,
problem))
{
if (isCheckGoalBeforeAddingToFrontier())
{
if (SearchUtils.isGoalState(problem, fn))
{
setPathCost(fn.getPathCost());
return(SearchUtils.actionsFromNodes(fn
.getPathFromRoot()));
}
}
frontier.Enqueue(fn);
}
setQueueSize(frontier.Count);
}
// if the frontier is empty then return failure
return(failure());
}
/**
*
* @param problem
* @param frontier
* @return if goal found, the list of actions to the Goal. If already at the
* goal you will receive a List with a single NoOp Action in it. If
* fail to find the Goal, an empty list will be returned to indicate
* that the search failed.
*/
public virtual List<Action> search(Problem problem, Queue<Node> frontier)
{
this.frontier = frontier;
clearInstrumentation();
// initialize the frontier using the initial state of the problem
Node root = new Node(problem.getInitialState());
if (isCheckGoalBeforeAddingToFrontier())
{
if (SearchUtils.isGoalState(problem, root))
{
return SearchUtils.actionsFromNodes(root.getPathFromRoot());
}
}
frontier.Enqueue(root);
setQueueSize(frontier.Count);
while (!(frontier.Count==0))
{
// choose a leaf node and remove it from the frontier
Node nodeToExpand = popNodeFromFrontier();
setQueueSize(frontier.Count);
// Only need to check the nodeToExpand if have not already
// checked before adding to the frontier
if (!isCheckGoalBeforeAddingToFrontier())
{
// if the node contains a goal state then return the
// corresponding solution
if (SearchUtils.isGoalState(problem, nodeToExpand))
{
setPathCost(nodeToExpand.getPathCost());
return SearchUtils.actionsFromNodes(nodeToExpand
.getPathFromRoot());
}
}
// expand the chosen node, adding the resulting nodes to the
// frontier
foreach (Node fn in getResultingNodesToAddToFrontier(nodeToExpand,
problem))
{
if (isCheckGoalBeforeAddingToFrontier())
{
if (SearchUtils.isGoalState(problem, fn))
{
setPathCost(fn.getPathCost());
return SearchUtils.actionsFromNodes(fn
.getPathFromRoot());
}
}
frontier.Enqueue(fn);
}
setQueueSize(frontier.Count);
}
// if the frontier is empty then return failure
return failure();
}
// function RECURSIVE-BEST-FIRST-SEARCH(problem) returns a solution, or
// failure
public List<Action> search(Problem p) {
List<Action> actions = new List<Action>();
clearInstrumentation();
// RBFS(problem, MAKE-NODE(INITIAL-STATE[problem]), infinity)
Node n = new Node(p.getInitialState());
SearchResult sr = rbfs(p, n, evaluationFunction.f(n), INFINITY, 0);
if (sr.getOutcome() == SearchResult.SearchOutcome.SOLUTION_FOUND) {
Node s = sr.getSolution();
actions = SearchUtils.actionsFromNodes(s.getPathFromRoot());
setPathCost(s.getPathCost());
}
// Empty List can indicate already at Goal
// or unable to find valid set of actions
return actions;
}
// function SIMULATED-ANNEALING(problem, schedule) returns a solution state
public List<Action> search(Problem p) {
clearInstrumentation();
outcome = SearchOutcome.FAILURE;
lastState = null;
// current <- MAKE-NODE(problem.INITIAL-STATE)
Node current = new Node(p.getInitialState());
Node next = null;
List<Action> ret = new List<Action>();
// for t = 1 to INFINITY do
int timeStep = 0;
while (!CancelableThread.currIsCanceled()) {
// temperature <- schedule(t)
double temperature = scheduler.getTemp(timeStep);
timeStep++;
// if temperature = 0 then return current
if (temperature == 0.0) {
if (SearchUtils.isGoalState(p, current)) {
outcome = SearchOutcome.SOLUTION_FOUND;
}
ret = SearchUtils.actionsFromNodes(current.getPathFromRoot());
lastState = current.getState();
break;
}
List<Node> children = expandNode(current, p);
if (children.Count > 0) {
// next <- a randomly selected successor of current
next = Util.selectRandomlyFromList(children);
// /\E <- next.VALUE - current.value
double deltaE = getValue(p, next) - getValue(p, current);
if (shouldAccept(temperature, deltaE)) {
current = next;
}
}
}
return ret;
}