changes for merge

npc/pirate/actions.py

@@ -4,7 +4,7 @@
 The module must contain a list called "exported_actions".  This list should
 contain any classes that you would like to add to the planner.
 
-To make it convienent, I have chosen to add the class to the list after each
+To make it convenient, I have chosen to add the class to the list after each
 declaration, although you may choose another way.
 """
 
@@ -80,7 +80,7 @@ class move_to_entity(ActionBuilder):
     """
 
     def get_actions(self, caller, memory):
-        here = get_position(caller, memory) 
+        here = get_position(caller, memory)
         visited = []
 
         for pct in memory.of_class(PositionPrecept):
@@ -109,7 +109,7 @@ def get_actions(self, caller, memory):
             if here == pct.position and pct.entity is not caller:
                 action = PickupAction(caller)
                 action.effects.append(HasItemGoal(pct.entity))
-                yield action 
+                yield action
 
 exported_actions.append(pickup)
 

pygoap/agent.py

@@ -97,7 +97,7 @@ def replan(self):
         s = [ g for g in s if g[0] > 0.0 ]
         s.sort(reverse=True)
 
-        debug("[agent] %s goals %s", self, s)
+        debug("[agent] %s has goals %s", self, s)
 
         start_action = NullAction
 

pygoap/blackboard.py

@@ -8,14 +8,14 @@ class MemoryManager(set):
     """
     Store and manage precepts.
     
-    shared blackboards violate reality in that multiple agents share the same
-    thoughts, to extend the metaphore.  but, the advantage of this is that in
+    Shared blackboards violate reality in that multiple agents share the same
+    thoughts, to extend the metaphor.  But, the advantage of this is that in
     a real-time simulation, it gives the player the impression that the agents
-    are able to collobroate in some meaningful way, without a significant
-    impact in performace.
+    are able to collaborate in some meaningful way, without a significant
+    impact in performance.
 
-    that being said, i have chosen to restrict blackboards to a per-agent
-    basis.  this library is meant for rpgs, where the action isn't real-time
+    That being said, i have chosen to restrict blackboards to a per-agent
+    basis.  This library is meant for RPGs, where the action isn't real-time
     and would require a more realistic simulation of intelligence.
     """
 

pygoap/goals.py

@@ -3,7 +3,7 @@
 planning.  Goals are known to the agent and are constantly monitored and
 evaluated.  The agent will attempt to choose the most relevant goal for it's
 state (determined by the blackboard) and then the planner will determine a
-plan for the agent to follw that will (possibly) satisfy the chosen goal.
+plan for the agent to follow that will (possibly) satisfy the chosen goal.
 
 See the modules effects.py and goals.py to see how these are used.
 
@@ -15,6 +15,7 @@
 """
 
 from memory import MemoryManager
+from environment2d import distance
 from precepts import *
 import sys, logging
 
@@ -186,13 +187,13 @@ class PositionGoal(GoalBase):
 
     def test(self, memory):
         """
-        search memory for last known position of the target if target is not
-        in agent's memory return 0.0.
+        search memory for last known position of the target
+        if target is not in agent's memory then return 0.0.
 
-        do pathfinding and determine if the target is accessable
-            - if not return 0.0
+        do pathfinding and determine if the target is accessible
+        if not return 0.0
 
-        determine the distance required to travel to the target
+        Determine the distance required to travel to the target
         return 1.0 if the target is reachable
         """