// Need to override search() method so that I can re-initialize
// the explored set should multiple calls to search be made.
public override List<Action> search(Problem problem, Queue<Node> frontier)
{
// initialize the explored set to be empty
explored.Clear();
frontierState.Clear();
return base.search(problem, frontier);
}
// 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);
}
public void testMultiGoalProblem()
{
Map romaniaMap = new SimplifiedRoadMapOfPartOfRomania();
Problem problem = new Problem(SimplifiedRoadMapOfPartOfRomania.ARAD,
MapFunctionFactory.getActionsFunction(romaniaMap),
MapFunctionFactory.getResultFunction(), new DualMapGoalTest(
SimplifiedRoadMapOfPartOfRomania.BUCHAREST,
SimplifiedRoadMapOfPartOfRomania.HIRSOVA),
new MapStepCostFunction(romaniaMap));
Search search = new BreadthFirstSearch(new GraphSearch());
SearchAgent agent = new SearchAgent(problem, search);
Assert
.Equals(
"[Action[name==moveTo, location==Sibiu], Action[name==moveTo, location==Fagaras], Action[name==moveTo, location==Bucharest], Action[name==moveTo, location==Urziceni], Action[name==moveTo, location==Hirsova]]",
agent.getActions().ToString());
Assert.Equals(5, agent.getActions().Count);
Assert.Equals("14", agent.getInstrumentation()[
"nodesExpanded"]);
Assert.Equals("1", agent.getInstrumentation()[
"queueSize"]);
Assert.Equals("5", agent.getInstrumentation()[
"maxQueueSize"]);
}
/**
*
* @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();
}
public BidirectionalMapProblem(Map aMap, String initialState,
String goalState) : base(initialState, MapFunctionFactory.getActionsFunction(aMap),
MapFunctionFactory.getResultFunction(), new DefaultGoalTest(
goalState), new MapStepCostFunction(aMap))
{
;
map = aMap;
reverseProblem = new Problem(goalState, MapFunctionFactory
.getActionsFunction(aMap), MapFunctionFactory
.getResultFunction(), new DefaultGoalTest(initialState),
new MapStepCostFunction(aMap));
}
protected override List<Action> search(Problem problem) {
List<Action> actions = new List<Action>();
try {
List<Action> sactions = _search.search(problem);
foreach (Action action in sactions) {
actions.Add(action);
}
}
catch (System.Exception ex)
{
System.Diagnostics.Debug.WriteLine(ex.ToString());
}
return actions;
}
// 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;
}
public override List<Node> getResultingNodesToAddToFrontier(Node nodeToExpand,
Problem problem)
{
addToFrontier.Clear();
// add the node to the explored set
explored.Add(nodeToExpand.getState());
// expand the chosen node, adding the resulting nodes to the frontier
foreach (Node cfn in expandNode(nodeToExpand, problem))
{
Node frontierNode = frontierState[cfn.getState()];
bool yesAddToFrontier = false;
// only if not in the frontier or explored set
if (null == frontierNode && !explored.Contains(cfn.getState()))
{
yesAddToFrontier = true;
}
else if (null != frontierNode
&& null != replaceFrontierNodeAtStateCostFunction
&& replaceFrontierNodeAtStateCostFunction.Compare(cfn,
frontierNode) < 0)
{
// child.STATE is in frontier with higher cost
// replace that frontier node with child
yesAddToFrontier = true;
// Want to replace the current frontier node with the child
// node therefore mark the child to be added and remove the
// current fontierNode
removeNodeFromFrontier(frontierNode);
// Ensure removed from add to frontier as well
// as 1 or more may reach the same state at the same time
addToFrontier.Remove(frontierNode);
}
if (yesAddToFrontier)
{
addToFrontier.Add(cfn);
frontierState.Add(cfn.getState(), cfn);
}
}
return addToFrontier;
}
public static bool isGoalState(Problem p, Node n)
{
bool isGoal = false;
GoalTest gt = p.getGoalTest();
if (gt.isGoalState(n.getState()))
{
if (gt is SolutionChecker)
{
isGoal = ((SolutionChecker)gt).isAcceptableSolution(
SearchUtils.actionsFromNodes(n.getPathFromRoot()), n
.getState());
}
else
{
isGoal = true;
}
}
return isGoal;
}
public List<Node> expandNode(Node node, Problem problem)
{
List<Node> childNodes = new List<Node>();
ActionsFunction actionsFunction = problem.getActionsFunction();
ResultFunction resultFunction = problem.getResultFunction();
StepCostFunction stepCostFunction = problem.getStepCostFunction();
foreach (Action action in actionsFunction.actions(node.getState()))
{
System.Object successorState = resultFunction.result(node.getState(),
action);
double stepCost = stepCostFunction.c(node.getState(), action,
successorState);
childNodes.Add(new Node(successorState, node, action, stepCost));
}
metrics.set(METRIC_NODES_EXPANDED, metrics
.getInt(METRIC_NODES_EXPANDED) + 1);
return childNodes;
}
// function ITERATIVE-DEEPENING-SEARCH(problem) returns a solution, or
// failure
public List<Action> search(Problem p)
{
iterationMetrics.set(METRIC_NODES_EXPANDED, 0);
iterationMetrics.set(PATH_COST, 0);
// for depth = 0 to infinity do
for (int i = 0; i <= infinity; i++)
{
// result <- DEPTH-LIMITED-SEARCH(problem, depth)
DepthLimitedSearch dls = new DepthLimitedSearch(i);
List<Action> result = dls.search(p);
iterationMetrics.set(METRIC_NODES_EXPANDED, iterationMetrics
.getInt(METRIC_NODES_EXPANDED)
+ dls.getMetrics().getInt(METRIC_NODES_EXPANDED));
// if result != cutoff then return result
if (!dls.isCutOff(result))
{
iterationMetrics.set(PATH_COST, dls.getPathCost());
return result;
}
}
return failure();
}
// 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;
}
protected abstract List<Action> search(Problem problem);
//
// PRIVATE METHODS
//
// function RECURSIVE-DLS(node, problem, limit) returns a solution, or
// failure/cutoff
private List<Action> recursiveDLS(Node node, Problem problem, int limit)
{
// if problem.GOAL-TEST(node.STATE) then return SOLUTION(node)
if (SearchUtils.isGoalState(problem, node))
{
setPathCost(node.getPathCost());
return SearchUtils.actionsFromNodes(node.getPathFromRoot());
}
else if (0 == limit)
{
// else if limit = 0 then return cutoff
return cutoff();
}
else
{
// else
// cutoff_occurred? <- false
bool cutoff_occurred = false;
// for each action in problem.ACTIONS(node.STATE) do
foreach (Node child in this.expandNode(node, problem))
{
// child <- CHILD-NODE(problem, node, action)
// result <- RECURSIVE-DLS(child, problem, limit - 1)
List<Action> result = recursiveDLS(child, problem, limit - 1);
// if result = cutoff then cutoff_occurred? <- true
if (isCutOff(result))
{
cutoff_occurred = true;
}
else if (!isFailure(result))
{
// else if result != failure then return result
return result;
}
}
// if cutoff_occurred? then return cutoff else return failure
if (cutoff_occurred)
{
return cutoff();
}
else
{
return failure();
}
}
}
public abstract List<Node> getResultingNodesToAddToFrontier(
Node nodeToExpand, Problem p);
public List<Action> search(Problem p)
{
return search.search(p, new LIFOQueue<Node>());
}
public SearchAgent(Problem p, Search search)
{
actionList = search.search(p);
actionIterator = actionList.GetEnumerator();
searchMetrics = search.getMetrics();
}
private double getValue(Problem p, Node n) {
// assumption greater heuristic value =>
// HIGHER on hill; 0 == goal state;
// SA deals with gardient DESCENT
return -1 * hf.h(n.getState());
}
//
// PRIVATE METHODS
//
// function RBFS(problem, node, f_limit) returns a solution, or failure and
// a new f-cost limit
private SearchResult rbfs(Problem p, Node n, double node_f, double fLimit,
int recursiveDepth) {
setMaxRecursiveDepth(recursiveDepth);
// if problem.GOAL-TEST(node.STATE) then return SOLUTION(node)
if (SearchUtils.isGoalState(p, n)) {
return new SearchResult(n, fLimit);
}
// successors <- []
// for each action in problem.ACTION(node.STATE) do
// add CHILD-NODE(problem, node, action) into successors
List<Node> successors = expandNode(n, p);
// if successors is empty then return failure, infinity
if (0 == successors.Count) {
return new SearchResult(null, INFINITY);
}
double[] f = new double[successors.Count];
// for each s in successors do
// update f with value from previous search, if any
int size = successors.Count;
for (int s = 0; s < size; s++) {
// s.f <- max(s.g + s.h, node.f)
f[s] = Math.max(evaluationFunction.f(successors.get(s)), node_f);
}
// repeat
while (true) {
// best <- the lowest f-value node in successors
int bestIndex = getBestFValueIndex(f);
// if best.f > f_limit then return failure, best.f
if (f[bestIndex] > fLimit) {
return new SearchResult(null, f[bestIndex]);
}
// if best.f > f_limit then return failure, best.f
int altIndex = getNextBestFValueIndex(f, bestIndex);
// result, best.f <- RBFS(problem, best, min(f_limit, alternative))
SearchResult sr = rbfs(p, successors.get(bestIndex), f[bestIndex],
Math.min(fLimit, f[altIndex]), recursiveDepth + 1);
f[bestIndex] = sr.getFCostLimit();
// if result != failure then return result
if (sr.getOutcome() == SearchResult.SearchOutcome.SOLUTION_FOUND) {
return sr;
}
}
}
//
// PRIVATE METHODS
//
private Node getHighestValuedNodeFrom(List<Node> children, Problem p) {
double highestValue = Double.NEGATIVE_INFINITY;
Node nodeWithHighestValue = null;
for (int i = 0; i < children.Count; i++) {
Node child = (Node) children.get(i);
double value = getValue(child);
if (value > highestValue) {
highestValue = value;
nodeWithHighestValue = child;
}
}
return nodeWithHighestValue;
}
public override List<Node> getResultingNodesToAddToFrontier(Node nodeToExpand,
Problem problem)
{
// expand the chosen node, adding the resulting nodes to the frontier
return expandNode(nodeToExpand, problem);
}
public List<Action> search(Problem p) {
return search.search(p, new PriorityQueue<Node>(5, getComparator()));
}
protected abstract List <Action> search(Problem problem);
public abstract List <Node> getResultingNodesToAddToFrontier(
Node nodeToExpand, Problem p);
