/**
* Return the sum of the integers in the list
*
* @param integerMap - The map of integers
* @return - the sum of integers in the list
*/
private int sumOf(Map<Integer, Integer> integerList) {
int sum = 0; // The sum
for (Integer current : integerList.keySet()) {
sum += integerList.get(current);
}
return sum;
}
/**
* Find out the maximum value for a given map of actions
*
* @param actions - The map of actions to their values
* @return Return the action with the largest value out of all the actions
*/
private Action maxArg(Map<Action, Double> actions) {
Action largestValue = null; // The largest value
for (Action current : actions.keySet()) {
if (largestValue == null || (actions.get(largestValue) < actions.get(current))) {
largestValue = current;
}
}
return largestValue;
}
/**
* Make a copy of a policy
*
* @param Map<State, Action> newPolicy - The new policy
*/
private void copyPolicy(Map<State, Action> newPolicy) {
/* Containers for clones */
State current;
Action currentAction;
this.policy = new HashMap<State, Action>();
for (State newState : newPolicy.keySet()) {
current = new State(newState.getState());
current.setCost(newState.getTemporaryCost());
currentAction = new Action(newPolicy.get(newState).getPurchases());
this.policy.put(current, currentAction);
}
}
/**
* Transition function. Currently, we only get the list of probabilities of each item.
*
* @param current - The current state
* @param action - The action
* @param possible - The possible state
* @return The list of probabilities where each index refers to the probability of that item
*/
private List<Double> transition(State current, Action action, State possible) {
List<Double> probs = new ArrayList<Double>(); // Probabilities
Map<Integer, Integer> currentStock, purchase, possibleStock; // Maps
double currentProb; // The current probability
Matrix currentMatrix; // The current probability matrix
int row, column; // The row and column
for (int i = 0; i < current.getState().size(); ++i) {
currentProb = 0.0;
currentStock = current.getState();
purchase = action.getPurchases();
possibleStock = possible.getState();
row = currentStock.get(i) + purchase.get(i);
column = row - possible.getState().get(i);
currentMatrix = this.probabilities.get(i);
if (column < 0
|| column >= currentMatrix.getNumCols()
|| row >= currentMatrix.getNumRows()) { // Invalid state
probs.add(0.0);
continue;
}
if (possibleStock.get(i) > 0
|| (possibleStock.get(i) == 0 && column == 0)) { // Sufficiently provided
currentProb = currentMatrix.get(row, column);
} else if (possibleStock.get(i) == 0 && column > 0) {
// Range of probabilities because user could have eaten plenty
for (int j = column; j < currentMatrix.getNumCols(); ++j) {
currentProb += currentMatrix.get(row, j);
}
}
probs.add(currentProb);
}
return probs;
}
/** Generate all possible actions */
private void generateAllPossibleActions() {
double startTime, endTime; // Timer for generating states
Map<Integer, Integer> action; // Action
int maxSum = this.fridge.getMaxPurchase(); // The maximum amount we can purchase
int maxIndex = this.fridge.getMaxTypes() - 1; // The maximum index of an action
System.out.println("Generating all possible actions");
startTime = endTime = Global.currentTime(); /* Set the time */
action = new HashMap<Integer, Integer>();
/* Generate zero case */
for (int i = 0; i < (maxIndex + 1); ++i) {
action.put(i, 0);
}
this.possibleActions.add(new Action(action));
System.out.println("Size of action: " + action.size());
while ((endTime - startTime) < this.MAX_GENERATION_TIME) {
if (this.fridge.getMaxTypes() <= 0) {
System.err.println("Invalid number of item types");
System.exit(10);
} else if (this.fridge.getMaxTypes() == 1) { // Only have 1 type of item
break;
} else { // Fridge has 2 or more types of items
for (int i = maxSum; i >= 0; --i) {
for (int j = 0; j < (maxIndex + 1); ++j) {
recursiveGeneration(1, maxSum, i, j, action, this.fridge.getMaxPurchase());
for (int k = 0; k < (maxIndex + 1); ++k) { // Reset list
action.put(k, 0);
}
}
endTime = Global.currentTime();
if ((endTime - startTime) >= this.MAX_GENERATION_TIME) {
break;
}
}
}
endTime = Global.currentTime(); // Get current time
this.timeRemaining -= (endTime - startTime);
System.out.println("Time remaining: " + this.timeRemaining);
break;
}
}
public List<Integer> generateShoppingList(List<Integer> inventory, int numWeeksLeft) {
State current; // current state
Map<Integer, Integer> purchases = new HashMap<Integer, Integer>(); // Purchases
Map<Integer, Integer> map = new HashMap<Integer, Integer>(); // Mapping of integers
List<Integer> shopping = new ArrayList<Integer>(); // Shopping items
for (int i = 0; i < inventory.size(); ++i) {
map.put(i, inventory.get(i));
}
current = new State(map);
purchases = this.policy.get(current).getPurchases();
for (int i = 0; i < inventory.size(); ++i) {
shopping.add(purchases.get(i));
}
return shopping;
}
/** Generate all the possible states */
private void generateAllPossibleStates() {
double startTime, endTime; // Timer for generating states
Map<Integer, Integer> state; // Action
int maxSum = this.fridge.getCapacity(); // The maximum amount we can have in a state
int maxIndex = this.fridge.getMaxTypes() - 1; // The maximum index of a state
System.out.println("Generating all possible states");
startTime = endTime = Global.currentTime(); /* Set the time */
state = new HashMap<Integer, Integer>();
/* Generate zero case */
for (int i = 0; i < (maxIndex + 1); ++i) {
state.put(i, 0);
}
this.possibleStates.add(new State(state));
System.out.println("Size of state: " + state.size());
while ((endTime - startTime) < this.MAX_GENERATION_TIME) {
if (this.fridge.getMaxTypes() <= 0) {
System.exit(10);
} else if (this.fridge.getMaxTypes() == 1) { // Only have 1 type of item
break;
} else { // Fridge has 2 or more types of items
for (int i = maxSum; i >= 0; --i) {
for (int j = 0; j < (maxIndex + 1); ++j) {
recursiveGeneration(0, maxSum, i, j, state, this.fridge.getMaxItemsPerType());
for (int k = 0; k < (maxIndex + 1); ++k) { // Reset list
state.put(k, 0);
}
}
endTime = Global.currentTime();
if ((endTime - startTime) >= this.MAX_GENERATION_TIME) {
break;
}
}
}
endTime = Global.currentTime(); // Get current time
this.timeRemaining -= (endTime - startTime);
System.out.println("Time remaining: " + this.timeRemaining);
break;
}
}
/**
* Recursively generate list based on given values
*
* @param int generateType - The type we are currently generating
* @param int maxSum - The maximum sum
* @param int remaining - The remaining value
* @param int currentIndex - The current index we are looking at
* @param Map<Integer, Integer> currentMap - Current map being modified
* @param int maxVal - The maximum value
*/
private void recursiveGeneration(
int generateType,
int maxSum,
int remaining,
int currentIndex,
Map<Integer, Integer> currentMap,
int maxVal) {
int localCurrentIndex = currentIndex; // The current index
if (remaining < 0 || currentIndex > (this.fridge.getMaxTypes() - 1)) {
addToList(generateType, currentMap);
return;
} else {
for (int i = remaining; i >= 0; --i) {
if (i >= maxVal) { // Too much remaining
currentMap.put(currentIndex, maxVal);
addToList(generateType, currentMap);
recursiveGeneration(
generateType,
maxSum - maxVal,
maxSum - maxVal,
localCurrentIndex + 1,
currentMap,
maxVal);
} else if (i == 0 && maxSum == 0) { // We are done
clearFromCurrent(currentIndex, currentMap);
addToList(generateType, currentMap);
return;
} else { // Just the right amount
currentMap.put(currentIndex, i);
addToList(generateType, currentMap);
recursiveGeneration(
generateType, maxSum - i, maxSum - i, localCurrentIndex + 1, currentMap, maxVal);
}
}
}
}
/** Generate optimal policy */
private void generateOptimalPolicy() {
double startTime, currentTime; // Timer things
boolean alreadyRunThrough = false; // Record if we've already done one run
Set<State> toLookup; // The states to lookup
Map<Action, Double> differentValues =
new HashMap<Action, Double>(); // The different values for the current state
Map<State, Action> newPolicy = new HashMap<State, Action>(); // New policy
State newState; // New state for new policy
Action best; // The best action
startTime = Global.currentTime();
currentTime = Global.currentTime();
while ((currentTime - startTime) <= this.timeRemaining) {
if (alreadyRunThrough) {
toLookup = this.policy.keySet();
} else {
toLookup = this.possibleStates;
}
for (State currentState : toLookup) {
differentValues.clear(); // Reset different values
for (Action currentAction : this.possibleActions) {
if (!validAction(currentAction, currentState)) {
continue;
}
differentValues.put(
currentAction, valueGeneration(currentState, currentAction, toLookup));
}
best = maxArg(differentValues);
if (isBetterPolicy(currentState, differentValues.get(best))) {
newState = new State(currentState.getState());
newState.setTemporaryCost(differentValues.get(best));
newPolicy.put(newState, best);
}
}
if (CheckDifference(0.1, newPolicy)) {
copyPolicy(newPolicy);
newPolicy.clear();
alreadyRunThrough = true;
} else {
currentTime = Global.currentTime();
break;
}
}
}
/**
* Checks if the difference between the values of the previous policy and the new policy are <=
* val.
*
* <p>Also reassigns the old policy
*
* @param double val - The difference
* @param Map<State, Action> newPolicy - The new policy
* @return true if the minimum difference > val. false otherwise
*/
private boolean CheckDifference(double val, Map<State, Action> newPolicy) {
Double currDiff, minDiff = null; // The minimum and current difference
if (this.policy.size() != this.possibleStates.size()) { // Previous policy wasn't assigned yet
return true;
}
for (State current : newPolicy.keySet()) {
for (State old : this.policy.keySet()) {
if (current.equals(old)) {
currDiff = Math.abs(current.getTemporaryCost() - old.getCost());
if (minDiff == null || currDiff <= minDiff) {
minDiff = currDiff;
}
break;
}
}
}
if (minDiff > val) {
return true;
}
return false;
}
/**
* Set to 0 everything from index current to size of map
*
* @param int current - The current index
* @param Map<Integer, Integer> mapToClear - The map to clear
*/
private void clearFromCurrent(int current, Map<Integer, Integer> mapToClear) {
for (int i = current; i < mapToClear.size(); ++i) {
mapToClear.put(i, 0);
}
}
