diff --git a/aimaPy/csp.py b/aimaPy/csp.py
index 414f69fb9..59dfb8b1b 100644
--- a/aimaPy/csp.py
+++ b/aimaPy/csp.py
@@ -601,7 +601,7 @@ def show_cell(cell): return str(assignment.get(cell, '.'))
         def abut(lines1, lines2): return list(
             map(' | '.join, list(zip(lines1, lines2))))
         print('\n------+-------+------\n'.join(
-            '\n'.join(reduce(abut, list(map(show_box, brow)))) for brow in self.bgri))
+            '\n'.join(reduce(abut, list(map(show_box, brow)))) for brow in self.bgrid))
 #______________________________________________________________________________
 # The Zebra Puzzle
 
diff --git a/aimaPy/search.py b/aimaPy/search.py
index dc29e9e85..9cd459391 100644
--- a/aimaPy/search.py
+++ b/aimaPy/search.py
@@ -374,8 +374,35 @@ def simulated_annealing(problem, schedule=exp_schedule()):
 
 
 def and_or_graph_search(problem):
+    """Used when the environment is  nondeterministic and completely observable
+    Contains OR nodes where the agent is free to choose any action
+    After every action there is an AND node which contains all possible states the agent may reach due to stochastic nature of environment
+    The agent must be able to handle all possible states of the AND node(as it may end up in any of them)
+    returns a conditional plan to reach goal state, or failure if the former is not possible"""
     "[Fig. 4.11]"
-    unimplemented()
+
+    #functions used by and_or_search
+    def or_search(state, problem, path):
+        if problem.goal_test(state):
+            return {}
+        if state in path:
+            return None
+        for action in problem.action(state):
+            plan = and_search(problem.result(state, action), problem, path + [state,])
+            if not plan == None:
+                return [action, plan]
+
+    def and_search(states, problem, path):
+        "returns plan in form of dictionary where we take action plan[s] if we reach state s"
+        plan=dict()
+        for s in states:
+            plan[s] = or_search(s, problem, path)
+            if plan[s] == None:
+                return None
+        return plan
+
+    #body of and or search
+    return or_search(problem.initial, problem, [])
 
 
 def online_dfs_agent(s1):
diff --git a/tests/utils_test.py b/tests/utils_test.py
index 2f5492e58..eb63448bb 100644
--- a/tests/utils_test.py
+++ b/tests/utils_test.py
@@ -128,10 +128,6 @@ def test_clip():
     assert [clip(x, 0, 1) for x in [-1, 0.5, 10]] == [0, 0.5, 1]
 
 
-def test_vector_clip():
-    assert vector_clip((-1, 10), (0, 0), (9, 9)) == (0, 9)
-
-
 def test_caller():
     assert caller(0) == 'caller'