diff --git a/README.md b/README.md
index 41d08f431..5adc57f63 100644
--- a/README.md
+++ b/README.md
@@ -64,7 +64,7 @@ Here is a table of algorithms, the figure, name of the algorithm in the book and
 | 2.7    | Table-Driven-Agent                | `TableDrivenAgent`            | [`agents.py`][agents]           | Done | Included |
 | 2.8    | Reflex-Vacuum-Agent               | `ReflexVacuumAgent`           | [`agents.py`][agents]           | Done | Included |
 | 2.10   | Simple-Reflex-Agent               | `SimpleReflexAgent`           | [`agents.py`][agents]           | Done | Included |
-| 2.12   | Model-Based-Reflex-Agent          | `ReflexAgentWithState`        | [`agents.py`][agents]           |      | Included |
+| 2.12   | Model-Based-Reflex-Agent          | `ReflexAgentWithState`        | [`agents.py`][agents]           | Done | Included |
 | 3      | Problem                           | `Problem`                     | [`search.py`][search]           | Done | Included |
 | 3      | Node                              | `Node`                        | [`search.py`][search]           | Done | Included |
 | 3      | Queue                             | `Queue`                       | [`utils.py`][utils]             | Done | No Need  |
diff --git a/agents.py b/agents.py
index eb085757a..d343fd55a 100644
--- a/agents.py
+++ b/agents.py
@@ -152,8 +152,8 @@ def ModelBasedReflexAgentProgram(rules, update_state, model):
     def program(percept):
         program.state = update_state(program.state, program.action, percept, model)
         rule = rule_match(program.state, rules)
-        action = rule.action
-        return action
+        program.action = rule.action
+        return program.action
     program.state = program.action = None
     return program
 
diff --git a/tests/test_agents.py b/tests/test_agents.py
index ded9b7d95..ea91f7eab 100644
--- a/tests/test_agents.py
+++ b/tests/test_agents.py
@@ -3,7 +3,7 @@
 from agents import Agent
 from agents import ReflexVacuumAgent, ModelBasedVacuumAgent, TrivialVacuumEnvironment, compare_agents,\
                    RandomVacuumAgent, TableDrivenVacuumAgent, TableDrivenAgentProgram, RandomAgentProgram, \
-		   SimpleReflexAgentProgram, rule_match
+		   SimpleReflexAgentProgram, rule_match, ModelBasedReflexAgentProgram
 
 
 random.seed("aima-python")
@@ -164,6 +164,64 @@ def interpret_input(state):
     # check final status of the environment
     assert environment.status == {(1,0):'Clean' , (0,0) : 'Clean'}
 
+def test_ModelBasedReflexAgentProgram():
+
+    loc_A = (0, 0)
+    loc_B = (1, 0)
+
+    model = {loc_A: None, loc_B: None}
+
+    class Rule:
+        def __init__(self, state, action):
+            self.__state = state
+            self.action = action
+
+        def matches(self, state):
+            return self.__state == state
+
+    # create rules for a two state Vacuum Environment
+    rules = [Rule((loc_A, "Dirty"), "Suck"), Rule((loc_A, "Clean"), "Right"),
+             Rule((loc_B, "Dirty"), "Suck"), Rule((loc_B, "Clean"), "Left")]
+
+    def update_state(state, action, percept, model):
+        loc, status = percept
+
+        # the other location
+        loc2 = tuple(map(lambda x: x[0]-x[1], zip((1,0), loc)))
+
+        # initial guess of the other location
+        if not state or not action or not model[loc2]:
+            model[loc2] = random.choice(['Dirty', 'Clean'])
+
+        model[loc] = status
+
+        # the model think environment will keep clean if agent chose to suck last step
+        if action == 'Suck':
+            state = percept
+            return state
+
+        # rubbish may appears suddenly, so the model guess randomly
+        if status == 'Clean':
+            status = random.choice(['Dirty', 'Clean'])
+            model[loc] = status
+
+        # move right or left will not influence the environment
+        state = (loc, model[loc])
+        return state
+
+    # create a program and then an object of the ModelBasedReflexAgentProgram
+
+    program = ModelBasedReflexAgentProgram(rules, update_state, model)
+    agent = Agent(program)
+
+    # create an object of TrivialVacuumEnvironment
+    environment = TrivialVacuumEnvironment()
+    # add agent to the environment
+    environment.add_thing(agent)
+    # run the environment
+    environment.run()
+    # check final status of the environment
+    assert environment.status == {(1, 0): 'Clean', (0, 0): 'Clean'}
 
 def test_ModelBasedVacuumAgent() :
     # create an object of the ModelBasedVacuumAgent
@@ -227,4 +285,4 @@ def constant_prog(percept):
         return percept
     agent = Agent(constant_prog)
     result = agent.program(5)
-    assert result == 5
+    assert result == 5
\ No newline at end of file