Exemplo n.º 1
0
def AStar(initial_state):
    global COUNT, BACKLINKS
    # priority queue with respective priority
    # add any auxiliary data structures as needed
    OPEN = PriorityQ()
    # inserts the initial state with a priority of 0 (priority for initial state is irrelevant to algorithm)
    OPEN.insert(initial_state, 0)
    CLOSED = []
    BACKLINKS[initial_state] = None

    while OPEN.__len__() > 0:
        # S = min-priority state (priority value gets discarded, only state is looked at)
        S = OPEN.deletemin()[0]
        while S in CLOSED:
            S = OPEN.deletemin()
        CLOSED.append(S)

        # DO NOT CHANGE THIS SECTION: beginning
        if Problem.GOAL_TEST(S):
            print(Problem.GOAL_MESSAGE_FUNCTION(S))
            path = backtrace(S)
            return path, Problem.PROBLEM_NAME
            # DO NOT CHANGE THIS SECTION: end

        COUNT += 1
        # if (COUNT % 32)==0:
        if True:
            # print(".",end="")
            # if (COUNT % 128)==0:
            if True:
                print("COUNT = " + str(COUNT))
                print("len(OPEN)=" + str(len(OPEN)))
                print("len(CLOSED)=" + str(len(CLOSED)))

        L = []
        # looks at all possible new states from operations on S
        # if the new state has not already been put on CLOSED, append to L
        for op in Problem.OPERATORS:
            if op.precond(S):
                new_state = op.state_transf(S)
                #print(new_state.__str__())
                if not occurs_in(new_state, CLOSED):
                    L.append(new_state)
                    BACKLINKS[new_state] = S

        # adds new states in L into OPEN with their priorities
        # if any state already occurs in OPEN...
        #   if L's state has a lower priority, change OPEN's state priority to L's
        #   otherwise, keep OPEN's state in OPEN, ignore L's
        for state in L:
            g_state = G(state)
            if OPEN.__contains__(state):
                if g_state < OPEN.getpriority(state):
                    OPEN.remove(state)
                else:
                    break
            OPEN.insert(state, g_state)
Exemplo n.º 2
0
def AStar(initial_state):
    global COUNT, BACKLINKS
    # priority queue with respective priority
    # add any auxiliary data structures as needed
    OPEN = PriorityQ()
    CLOSED = []
    BACKLINKS[initial_state] = None
    g = {initial_state: 0}

    OPEN.insert(initial_state, heuristics(initial_state))

    while not len(OPEN) == 0:
        S, f = OPEN.deletemin()
        while S in CLOSED:
            S, f = OPEN.deletemin()
        CLOSED.append(S)

        # DO NOT CHANGE THIS SECTION: begining
        if Problem.GOAL_TEST(S):
            print(Problem.GOAL_MESSAGE_FUNCTION(S))
            path = backtrace(S)
            return path, Problem.PROBLEM_NAME
        # DO NOT CHANGE THIS SECTION: end

        COUNT += 1
        print(COUNT)

        L = []
        for op in Problem.OPERATORS:
            if op.precond(S):
                new_state = op.state_transf(S)
                if not occurs_in(new_state, CLOSED):
                    L.append(new_state)
                    BACKLINKS[new_state] = S
                    if new_state not in g.keys():
                        g[new_state] = g[S] + 1

        for s2 in L:
            if s2 in OPEN:
                OPEN.remove(s2)

        for elt in L:
            OPEN.insert(elt, heuristics(elt) + g[elt])
Exemplo n.º 3
0
def AStar(initial_state):
    global COUNT, BACKLINKS
    OPEN = PriorityQ()  #currently discovered, not yet evaluated states
    CLOSED = []  #already evaluated states
    BACKLINKS[initial_state] = None  #Tracks most efficient previous step

    #Calculate F, G, H scores for Starting state
    initialize_scores(initial_state)

    #Only one state is known as of now
    OPEN.insert(initial_state, F_SCORE[initial_state])

    while OPEN.isEmpty() != True:
        S, priority = OPEN.deletemin()
        while S in CLOSED:
            S = OPEN.deletemin()
        CLOSED.append(S)

        # DO NOT CHANGE THIS SECTION: beginning
        if Problem.GOAL_TEST(S):
            print(Problem.GOAL_MESSAGE_FUNCTION(S))
            path = backtrace(S)
            return path, Problem.PROBLEM_NAME
            # DO NOT CHANGE THIS SECTION: end

        COUNT += 1
        if (COUNT % 32) == 0:
            #        if True:
            # print(".",end="")
            #            if (COUNT % 128*128)==0:
            if True:
                print("COUNT = " + str(COUNT))
                #print("len(OPEN)=" + str(len(OPEN))) #PriorityQ OPEN doesn't have len()
                print("len(CLOSED)=" + str(len(CLOSED)))

        for op in Problem.OPERATORS:
            if op.precond(S):
                new_state = op.state_transf(S)
                if not occurs_in(new_state,
                                 CLOSED):  #ignore already evaluated neighbors

                    #find tentative score of neighbor
                    tentative_g_score = G_SCORE[S] + 1

                    if new_state not in G_SCORE:  #Default INFINITY
                        BACKLINKS[
                            new_state] = S  #First known path to new_state

                    elif tentative_g_score <= G_SCORE[new_state]:
                        BACKLINKS[
                            new_state] = S  # Found better path to new_State

                    else:
                        continue  #current path is not the best path to the neighbor

                    G_SCORE[new_state] = tentative_g_score
                    F_SCORE[new_state] = G_SCORE[new_state] + h_score_fn(
                        new_state)

                    # Delete previous F-score in PriorityQ if it exists
                    if OPEN.__contains__(new_state):
                        OPEN.remove(new_state)

                    #Update PriorityQ with new priority
                    OPEN.insert(new_state, F_SCORE[new_state])

                # print(Problem.DESCRIBE_STATE(new_state))
        #print(OPEN)

    #Failure, if goal_test has not succeeded until now
    print("COULD NOT FIND GOAL")
    return