crafting done ?

ai_economist/foundation/base/base_agent.py

@@ -38,7 +38,7 @@ class BaseAgent:
 
         if idx is None:
             idx = 0
-
+        
         if multi_action_mode is None:
             multi_action_mode = False
 
@@ -64,6 +64,7 @@ class BaseAgent:
         self._registered_inventory = False
         self._registered_endogenous = False
         self._registered_components = False
+        self._setup = False # agent setup not completed 
         self._noop_action_dict = dict()
 
         # Special flag to allow logic for multi-action-mode agents
@@ -78,7 +79,13 @@ class BaseAgent:
     def idx(self):
         """Index used to identify this agent. Must be unique within the environment."""
         return self._idx
-
+    @property
+    def is_setup(self):
+        return self._setup
+        
+    def set_setup(self, set):
+        self._setup=set
+    
     def register_inventory(self, resources):
         """Used during environment construction to populate inventory/escrow fields."""
         if self._registered_inventory:

ai_economist/foundation/base/base_env.py

@@ -342,16 +342,11 @@ class BaseEnvironment(ABC):
             self._components_dict[component_object.name] = component_object
             self._shorthand_lookup[component_object.shorthand] = component_object
 
-        # Register the components with the agents
-        # to finish setting up their state/action spaces.
-        for agent in self.world.agents:
-            agent.register_inventory(self.resources)
-            agent.register_endogenous(self.endogenous)
-            agent.register_components(self._components)
+       
         self.world.planner.register_inventory(self.resources)
         self.world.planner.register_components(self._components)
-
-        self._agent_lookup = {str(agent.idx): agent for agent in self.all_agents}
+        self.apply_scenario_config_to_agents()
+       
 
         self._completions = 0
 
@@ -370,6 +365,16 @@ class BaseEnvironment(ABC):
         # To collate all the agents ('0', '1', ...) data during reset and step
         # into a single agent with index 'a'
         self.collate_agent_step_and_reset_data = collate_agent_step_and_reset_data
+    
+    def apply_scenario_config_to_agents(self):
+        # Register the components with the agents
+        # to finish setting up their state/action spaces.
+        for agent in self.world.agents:
+            agent.register_inventory(self.resources)
+            agent.register_endogenous(self.endogenous)
+            agent.register_components(self._components)
+        self._agent_lookup = {str(agent.idx): agent for agent in self.all_agents}
+        self.world.apply_agent_db_to_world()
 
     def _register_entities(self, entities):
         for entity in entities:
@@ -920,6 +925,7 @@ class BaseEnvironment(ABC):
         # Reset actions to that default.
         for agent in self.all_agents:
             agent.reset_actions()
+            agent.set_setup(True)
 
         # Produce observations
         obs = self._generate_observations(

ai_economist/foundation/base/world.py

@@ -382,7 +382,7 @@ class World:
         self._agent_class_idx_map={}
         #create agents
         self.create_agents(agent_composition)
-        
+
         self.maps = Maps(world_size, self.n_agents, world_resources, world_landmarks)
 
         planner_class = agent_registry.get("BasicPlanner")
@@ -410,7 +410,7 @@ class World:
                 self._agent_class_idx_map[k].append(str(self.n_agents))
                 self.n_agents+=1
 
-    def apply_agent_db(self):
+    def apply_agent_db_to_world(self):
         """Applys current agent db into lookup maps inside world and map itself. Enables insertion of new agents into existing env."""
         self.n_agents=len(self._agents)
         self._agent_class_idx_map={}