aimacode · delaray · Aug 12, 2018 · Aug 12, 2018 · Aug 12, 2018 · delaray
diff --git a/README.md b/README.md
@@ -140,7 +140,7 @@ Here is a table of algorithms, the figure, name of the algorithm in the book and
 | 19.2   | Current-Best-Learning             | `current_best_learning`       | [`knowledge.py`](knowledge.py)  | Done | Included |
 | 19.3   | Version-Space-Learning            | `version_space_learning`      | [`knowledge.py`](knowledge.py)  | Done | Included |
 | 19.8   | Minimal-Consistent-Det            | `minimal_consistent_det`      | [`knowledge.py`](knowledge.py)  | Done | Included |
-| 19.12  | FOIL                              | `FOIL_container`              | [`knowledge.py`](knowledge.py)  | Done |          |
+| 19.12  | FOIL                              | `FOIL_container`              | [`knowledge.py`](knowledge.py)  | Done | Included |
 | 21.2   | Passive-ADP-Agent                 | `PassiveADPAgent`             | [`rl.py`][rl]                   | Done | Included |
 | 21.4   | Passive-TD-Agent                  | `PassiveTDAgent`              | [`rl.py`][rl]                   | Done | Included |
 | 21.8   | Q-Learning-Agent                  | `QLearningAgent`              | [`rl.py`][rl]                   | Done | Included |

diff --git a/knowledge_FOIL.ipynb b/knowledge_FOIL.ipynb
@@ -587,10 +587,10 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "The algorithm produced almost the recursive rule: \n",
+    "The algorithm produced something close to the recursive rule: \n",
    " $$ Reach(x,y) \\Leftrightarrow [Conn(x,y)] \\: \\lor \\: [\\exists \\: z \\: \\: Reach(x,z) \\, \\land  \\, Reach(z,y)]$$\n",
    " \n",
-    "This is because the size of the example is small. "
+    "This happened because the size of the example is small. "
   ]
  }
 ],

diff --git a/planning.py b/planning.py
@@ -1144,6 +1144,7 @@ def simple_blocks_world_graphplan():
    return GraphPlan(simple_blocks_world()).execute()


+
 class HLA(Action):
    """
    Define Actions for the real-world (that may be refined further), and satisfy resource
@@ -1363,9 +1364,8 @@ def angelic_search(problem, hierarchy, initialPlan):
                guaranteed = problem.intersects_goal(pes_reachable_set) 
                if guaranteed and Problem.making_progress(plan, initialPlan):
                    final_state = guaranteed[0] # any element of guaranteed 
-                    #print('decompose')
                    return Problem.decompose(hierarchy, problem, plan, final_state, pes_reachable_set)
-                (hla, index) = Problem.find_hla(plan, hierarchy) # there should be at least one HLA/Angelic_HLA, otherwise plan would be primitive.
+                hla, index = Problem.find_hla(plan, hierarchy) # there should be at least one HLA/Angelic_HLA, otherwise plan would be primitive.
                prefix = plan.action[:index]
                suffix = plan.action[index+1:]
                outcome = Problem(Problem.result(problem.init, prefix), problem.goals , problem.actions )
@@ -1442,8 +1442,8 @@ def find_hla(plan, hierarchy):
                hla = plan.action[i] 
                index = i
                break
-        return (hla, index)
-	
+        return hla, index
+
    def making_progress(plan, initialPlan):
        """ 
        Prevents from infinite regression of refinements  

diff --git a/planning_angelic_search.ipynb b/planning_angelic_search.ipynb
@@ -11,8 +11,7 @@
    "-  problem is of type Problem \n",
    "-  hierarchy is a dictionary consisting of all the actions. \n",
    "-  initialPlan is an approximate description(optimistic and pessimistic) of the agents choices for the implementation. <br>\n",
-    "   It is a nested list, containing sequence a of actions with their optimistic and pessimistic\n",
-    "   description "
+    "   initialPlan contains a sequence of HLA's with angelic semantics"
   ]
  },
  {