unit 4

udacity/cs373/unit-4/a-star.py

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+# -----------
+# User Instructions:
+#
+# Modify the the search function so that it becomes
+# an A* search algorithm as defined in the previous
+# lectures.
+#
+# Your function should return the expanded grid
+# which shows, for each element, the count when
+# it was expanded or -1 if the element was never expanded.
+#
+# Your function only needs to work for a 5x6 grid.
+# You do not need to modify the heuristic.
+# ----------
+
+grid = [[0, 1, 0, 0, 0, 0],
+        [0, 1, 0, 0, 0, 0],
+        [0, 1, 0, 0, 0, 0],
+        [0, 1, 0, 0, 0, 0],
+        [0, 0, 0, 0, 1, 0]]
+
+heuristic = [[9, 8, 7, 6, 5, 4],
+            [8, 7, 6, 5, 4, 3],
+            [7, 6, 5, 4, 3, 2],
+            [6, 5, 4, 3, 2, 1],
+            [5, 4, 3, 2, 1, 0]]
+
+init = [0, 0]
+goal = [len(grid)-1, len(grid[0])-1]
+
+delta = [[-1, 0 ], # go up
+         [ 0, -1], # go left
+         [ 1, 0 ], # go down
+         [ 0, 1 ]] # go right
+
+delta_name = ['^', '<', 'v', '>']
+
+cost = 1
+
+# ----------------------------------------
+# modify code below
+# ----------------------------------------
+
+def search():
+    closed = [[0 for row in range(len(grid[0]))] for col in range(len(grid))]
+    closed[init[0]][init[1]] = 1
+
+    expand = [[-1 for row in range(len(grid[0]))] for col in range(len(grid))]
+    action = [[-1 for row in range(len(grid[0]))] for col in range(len(grid))]
+
+
+    x = init[0]
+    y = init[1]
+    g = 0
+    f = g + heuristic[x][y]
+
+    open = [[f, g, x, y]]
+
+    found = False  # flag that is set when search is complet
+    resign = False # flag set if we can't find expand
+    count = 0
+
+    while not found and not resign:
+        if len(open) == 0:
+            resign = True
+        else:
+            open.sort()
+            open.reverse()
+            next = open.pop()
+            x = next[2]
+            y = next[3]
+            g = next[1]
+            f = next[0]
+            expand[x][y] = count
+            count += 1
+
+            if x == goal[0] and y == goal[1]:
+                found = True
+            else:
+                for i in range(len(delta)):
+                    x2 = x + delta[i][0]
+                    y2 = y + delta[i][1]
+                    if x2 >= 0 and x2 < len(grid) and y2 >=0 and y2 < len(grid[0]):
+                        if closed[x2][y2] == 0 and grid[x2][y2] == 0:
+                            g2 = g + cost
+                            h2 = heuristic[x2][y2]
+                            f2 = g2 + h2
+                            open.append([f2, g2, x2, y2])
+                            closed[x2][y2] = 1
+    for i in range(len(expand)):
+        print expand[i]
+    return expand #Leave this line for grading purposes!
+
+
+search()

udacity/cs373/unit-4/dynamic-value.py

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+# ----------
+# User Instructions:
+# 
+# Create a function compute_value() which returns
+# a grid of values. Value is defined as the minimum
+# number of moves required to get from a cell to the
+# goal. 
+#
+# If it is impossible to reach the goal from a cell
+# you should assign that cell a value of 99.
+
+# ----------
+
+grid = [[0, 1, 0, 0, 0, 0],
+        [0, 1, 0, 0, 0, 0],
+        [0, 1, 1, 0, 0, 0],
+        [0, 1, 0, 1, 0, 0],
+        [0, 1, 0, 0, 1, 0]]
+
+init = [0, 0]
+goal = [len(grid)-1, len(grid[0])-1]
+
+delta = [[-1, 0 ], # go up
+         [ 0, -1], # go left
+         [ 1, 0 ], # go down
+         [ 0, 1 ]] # go right
+
+delta_name = ['^', '<', 'v', '>']
+
+cost_step = 1 # the cost associated with moving from a cell to an adjacent one.
+
+# ----------------------------------------
+# insert code below
+# ----------------------------------------
+
+def compute_value_r(out, x, y):
+    explore = []
+    current_value = out[x][y]
+    for i in range(len(delta)):
+        x2 = x + delta[i][0]
+        y2 = y + delta[i][1]
+        if x2 >= 0 and x2 < len(grid) and y2 >=0 and y2 < len(grid[0]):
+            if grid[x2][y2] == 0 and current_value < out[x2][y2]:
+                explore.append([x2, y2])
+                out[x2][y2] = out[x][y] + cost_step
+    for x in explore:
+        compute_value_r(out, x[0], x[1])
+
+def compute_value():
+    value = [[99 for row in range(len(grid[0]))] for col in range(len(grid))]
+    value[goal[0]][goal[1]] = 0
+    compute_value_r(value, goal[0], goal[1])
+    return value #make sure your function returns a grid of values as demonstrated in the previous video.
+
+out = compute_value()
+for i in out:
+    print i

udacity/cs373/unit-4/expansion.py

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+# -----------
+# User Instructions:
+# 
+# Modify the function search() so that it returns
+# a table of values called expand. This table
+# will keep track of which step each node was
+# expanded.
+#
+# For grading purposes, please leave the return
+# statement at the bottom.
+# ----------
+
+
+grid = [[0, 0, 1, 0, 0, 0],
+        [0, 0, 0, 0, 0, 0],
+        [0, 0, 1, 0, 1, 0],
+        [0, 0, 1, 0, 1, 0],
+        [0, 0, 1, 0, 1, 0]]
+
+init = [0, 0]
+goal = [len(grid)-1, len(grid[0])-1]
+
+delta = [[-1, 0 ], # go up
+         [ 0, -1], # go left
+         [ 1, 0 ], # go down
+         [ 0, 1 ]] # go right
+
+delta_name = ['^', '<', 'v', '>']
+
+cost = 1
+
+
+# ----------------------------------------
+# modify code below
+# ----------------------------------------
+
+def search():
+    closed = [[0 for row in range(len(grid[0]))] for col in range(len(grid))]
+    closed[init[0]][init[1]] = 1
+
+    expand = [[-1 for row in range(len(grid[0]))] for col in range(len(grid))]
+    iteration = 0
+
+    x = init[0]
+    y = init[1]
+    g = 0
+
+    open = [[g, x, y]]
+
+    found = False  # flag that is set when search is complete
+    resign = False # flag set if we can't find expand
+
+    while not found and not resign:
+        if len(open) == 0:
+            resign = True
+        else:
+            open.sort()
+            open.reverse()
+            next = open.pop()
+            x = next[1]
+            y = next[2]
+            g = next[0]
+
+            expand[x][y] = iteration
+            iteration += 1
+
+            if x == goal[0] and y == goal[1]:
+                found = True
+            else:
+                for i in range(len(delta)):
+                    x2 = x + delta[i][0]
+                    y2 = y + delta[i][1]
+                    if x2 >= 0 and x2 < len(grid) and y2 >=0 and y2 < len(grid[0]):
+                        if closed[x2][y2] == 0 and grid[x2][y2] == 0:
+                            g2 = g + cost
+                            open.append([g2, x2, y2])
+                            closed[x2][y2] = 1
+    return expand #Leave this line for grading purposes!
+
+
+
+
+print search()

udacity/cs373/unit-4/grid-search.py

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+# -----------
+# User Instructions:
+# 
+# Modify the function search() so that it returns
+# a table of values called expand. This table
+# will keep track of which step each node was
+# expanded.
+#
+# For grading purposes, please leave the return
+# statement at the bottom.
+# ----------
+
+
+grid = [[0, 0, 1, 0, 0, 0],
+        [0, 0, 0, 0, 0, 0],
+        [0, 0, 1, 0, 1, 0],
+        [0, 0, 1, 0, 1, 0],
+        [0, 0, 1, 0, 1, 0]]
+
+init = [0, 0]
+goal = [len(grid)-1, len(grid[0])-1]
+
+delta = [[-1, 0 ], # go up
+         [ 0, -1], # go left
+         [ 1, 0 ], # go down
+         [ 0, 1 ]] # go right
+
+delta_name = ['^', '<', 'v', '>']
+
+cost = 1
+
+
+# ----------------------------------------
+# modify code below
+# ----------------------------------------
+
+def search():
+    closed = [[0 for row in range(len(grid[0]))] for col in range(len(grid))]
+    closed[init[0]][init[1]] = 1
+
+    expand = [[-1 for row in range(len(grid[0]))] for col in range(len(grid))]
+    iteration = 0
+
+    x = init[0]
+    y = init[1]
+    g = 0
+
+    open = [[g, x, y]]
+
+    found = False  # flag that is set when search is complete
+    resign = False # flag set if we can't find expand
+
+    while not found and not resign:
+        if len(open) == 0:
+            resign = True
+        else:
+            open.sort()
+            open.reverse()
+            next = open.pop()
+            x = next[1]
+            y = next[2]
+            g = next[0]
+
+            expand[x][y] = iteration
+            iteration += 1
+
+            if x == goal[0] and y == goal[1]:
+                found = True
+            else:
+                for i in range(len(delta)):
+                    x2 = x + delta[i][0]
+                    y2 = y + delta[i][1]
+                    if x2 >= 0 and x2 < len(grid) and y2 >=0 and y2 < len(grid[0]):
+                        if closed[x2][y2] == 0 and grid[x2][y2] == 0:
+                            g2 = g + cost
+                            open.append([g2, x2, y2])
+                            closed[x2][y2] = 1
+    return expand #Leave this line for grading purposes!
+
+
+
+
+print search()