its not braking anymore

components/crafting.py

@@ -50,6 +50,7 @@ class Craft(BaseComponent):
         assert len(commodities)>0
         #setup commodities
         self.recip_map={}
+        self.commodities=[]
         for v in commodities:
             res_class=resource_registry.get(v)
             res=res_class()
@@ -80,11 +81,14 @@ class Craft(BaseComponent):
     def agent_can_build(self, agent, res):
         """Return True if agent can actually build in its current location."""
         # See if the agent has the resources necessary to complete the action
-        recipe= self.recip_map[res]
+        if res in self.recip_map:
-        for resource, cost in recipe.items():
+            recipe= self.recip_map[res]
-            if agent.state["inventory"][resource] < cost:
+            for resource, cost in recipe.items():
-                return False
+                if agent.state["inventory"][resource] < cost:
-        return True
+                    return False
+                else:
+                    return True
+        return False
 
     # Required methods for implementing components
     # --------------------------------------------
@@ -136,9 +140,10 @@ class Craft(BaseComponent):
 
             # Build! (If you can.)
             else:
+                action-=1
                 comm=self.commodities[action]
 
-                if self.agent_can_build(agent,comm.craft_recp):
+                if self.agent_can_build(agent,comm.name):
                     # Remove the resources
                     for resource, cost in comm.craft_recp.items():
                         agent.state["inventory"][resource] -= cost
@@ -211,7 +216,7 @@ class Craft(BaseComponent):
                 where metric_value is a scalar.
         """
         world = self.world
-
+        """
         build_stats = {a.idx: {"n_builds": 0} for a in world.agents}
         for builds in self.builds:
             for build in builds:
@@ -225,8 +230,8 @@ class Craft(BaseComponent):
 
         num_houses = np.sum(world.maps.get("House") > 0)
         out_dict["total_builds"] = num_houses
-
+    """
-        return out_dict
+        return {}
 
     def additional_reset_steps(self):
         """
@@ -257,7 +262,8 @@ class Craft(BaseComponent):
                     elif self.skill_dist == "pareto":
                         labour = 1
                         sampled_skill = np.random.pareto(2)
-                        amount = np.minimum(MSAB, MSAB * sampled_skill)
+
+                        amount = 1+np.minimum(MSAB,(MSAB-1) * (sampled_skill) )
                         labour_modifier = 1 - np.minimum(1 - MSLB, (1 - MSLB) * sampled_skill)
                     else:
                         raise NotImplementedError

components/external_market.py

@@ -107,8 +107,8 @@ class ExternalMarket(BaseComponent):
 
             # NO-OP!
             if action == 0:
-                pass
+                continue
-            action-=1
+           
             res_name=self.action_res_map[action]
             # Build! (If you can.)
        
@@ -163,10 +163,11 @@ class ExternalMarket(BaseComponent):
         # Mobile agents' build action is masked if they cannot build with their
         # current location and/or endowment
         for agent in self.world.agents:
-            mask=[]
+            if agent.name in self.agent_subclasses:
-            for res in self.market_demand:
+                mask=[]
-                mask.append(self.agent_can_sell(agent,res))
+                for res in self.market_demand:
-            masks[agent.idx] = mask
+                    mask.append(self.agent_can_sell(agent,res))
+                masks[agent.idx] = mask
 
         return masks
 
@@ -182,7 +183,7 @@ class ExternalMarket(BaseComponent):
                 where metric_value is a scalar.
         """
         world = self.world
-
+        """
         build_stats = {a.idx: {"n_builds": 0} for a in world.agents}
         for builds in self.builds:
             for build in builds:
@@ -196,8 +197,8 @@ class ExternalMarket(BaseComponent):
 
         num_houses = np.sum(world.maps.get("House") > 0)
         out_dict["total_builds"] = num_houses
-
+        """ 
-        return out_dict
+        return {}
 
     def additional_reset_steps(self):
         """

main.py

@@ -23,6 +23,7 @@ from envs.econ_wrapper import EconVecEnv
 from stable_baselines3.common.callbacks import BaseCallback
 import yaml
 import time
+from threading import Thread 
 
 env_config = {
     # ===== SCENARIO CLASS =====
@@ -61,7 +62,7 @@ env_config = {
     'allow_observation_scaling': True,
     'dense_log_frequency': 100, 
     'world_dense_log_frequency':1,
-    'energy_cost':0.21,
+    'energy_cost':0,
     'energy_warmup_method': "auto",
     'energy_warmup_constant': 4000,
     
@@ -116,7 +117,7 @@ eval_env_config = {
     'allow_observation_scaling': True,
     'dense_log_frequency': 10, 
     'world_dense_log_frequency':1, 
-    'energy_cost':0.21,
+    'energy_cost':0,
     'energy_warmup_method': "auto",
     'energy_warmup_constant': 4000,
     
@@ -223,23 +224,33 @@ baseEconWrapper=BaseEconWrapper(econ)
 baseEconWrapper.run()
 mobileRecieverEconWrapper=RecieverEconWrapper(base_econ=baseEconWrapper,agent_classname="BasicMobileAgent")
 tradeRecieverEconWrapper=RecieverEconWrapper(base_econ=baseEconWrapper,agent_classname="TradingAgent")
+sb3_traderConverter=SB3EconConverter(tradeRecieverEconWrapper,econ,"TradingAgent")
 sb3Converter=SB3EconConverter(mobileRecieverEconWrapper,econ,"BasicMobileAgent")
 #obs=sb3Converter.reset()
 #vecenv=EconVecEnv(env_config=env_config)
 
 monenv=VecMonitor(venv=sb3Converter,info_keywords=["social/productivity","trend/productivity"])
-
+montraidingenv=VecMonitor(venv=sb3_traderConverter)
 #normenv=VecNormalize(sb3Converter,norm_reward=False,clip_obs=1)
 #stackenv=vec_frame_stack.VecFrameStack(venv=monenv,n_stack=10)
 obs=monenv.reset()
 
 
+# define training functions
+def train(model,timesteps, econ_call,process_bar,name,db,index):
+    db[index]=model.learn(total_timesteps=timesteps,progress_bar=process_bar,reset_num_timesteps=False,tb_log_name=name,callback=TensorboardCallback(econ_call))
 
 
 
-runname="run_{}".format(int(np.random.rand()*100))
+# prepare training
+run_number=int(np.random.rand()*100)
+runname="run_{}".format(run_number)
+model_db=[] # object for storing model
+
 
 model = MaskablePPO("MlpPolicy",n_steps=int(env_config['episode_length']*2),ent_coef=0.1, vf_coef=0.8 ,gamma=0.95, learning_rate=5e-3,env=monenv, seed=225,verbose=1,device="cuda",tensorboard_log="./log")
+model_trade=MaskablePPO("MlpPolicy",n_steps=int(env_config['episode_length']*2),ent_coef=0.1, vf_coef=0.8 ,gamma=0.95, learning_rate=5e-3,env=montraidingenv, seed=225,verbose=1,device="cuda",tensorboard_log="./log")
+
 n_agents=econ.n_agents
 total_required_for_episode=n_agents*env_config['episode_length']
 print("this is run {}".format(runname))
@@ -249,11 +260,21 @@ eval_base_econ.run()
 eval_mobileRecieverEconWrapper=RecieverEconWrapper(eval_base_econ,"BasicMobileAgent")
 time.sleep(0.5)
 eval_sb3_converter=SB3EconConverter(eval_mobileRecieverEconWrapper,eval_econ,"BasicMobileAgent")
+
 while True:
     # Create Eval ENV
     vec_mon_eval=VecMonitor(venv=eval_sb3_converter)
     #Train
-    model=model.learn(total_timesteps=total_required_for_episode*10,progress_bar=True,reset_num_timesteps=False,tb_log_name=runname,callback=TensorboardCallback(econ=econ))
+    runname="run_{}_{}".format(run_number,"basic")
+
+    thread_model=Thread(target=train,args=(model,total_required_for_episode*10,econ,True,runname,model_db,0))
+    runname="run_{}_{}".format(run_number,"trader")
+    thread_model_traid=Thread(target=train,args=(model_trade,total_required_for_episode*10,econ,False,runname,model_db,1))
+    
+    thread_model.start()
+    thread_model_traid.start()
+    thread_model.join()
+    thread_model_traid.join()
     #normenv.save("temp-normalizer.ai")
 
     

wrapper/base_econ_wrapper.py

@@ -149,7 +149,8 @@ class BaseEconWrapper():
         self.action_edit_lock.acquire() # Start to submit action dict       
         for k,v in actions.items():
             if k in self.actor_actions.keys():
-               raise Exception("Actor action has already been submitted. {}".format(k))
+               print("Actor action has already been submitted. {}".format(k))
+               continue
             self.actor_actions[k]=v
         self.step_notifications[voter_id].clear()
         self.base_notification.set() #Alert base for action changes