This is getting better and better

db/production.yml

@@ -20,7 +20,7 @@ spec:
 #      Wood: 1
 
   - name: Food
-    amount: 500
+    amount: 5
     prod:
 #      Fuel: 1
       Fruit: 1

econ/agents/price_believe_distribute.py

@@ -17,7 +17,7 @@ class Price_Believe_Distribiute_Agent(Base_Distribution_Agent):
         self.lr_moment={i: 0 for i in range(len(self.exchanges))}
         self.open_orders = {i: [] for i in range(len(self.exchanges))}
         self.open_qty = 0
-        self.beta=0.6
+        self.beta=0.8
         self.lp_threshold=0.05
         self.hp_threshold=0.80
 
@@ -29,6 +29,8 @@ class Price_Believe_Distribiute_Agent(Base_Distribution_Agent):
             cx_id = self.select_best_cx()
 
             price = round(self.price_believe[cx_id],2)
+            if price==30.0:
+                print("Ple")
             if price < self.min_price:
                 price = self.min_price
             order = self.distribute_resource(

econ/business/Price_Believe_Business.py

@@ -14,13 +14,13 @@ class Price_Believe_Business(Business):
         self.expense_per_prod=-1
         self.income_per_unit = -1
         self.distribute = Price_Believe_Distribiute_Agent(
-            simulation, self, production["name"], exchange, 0.5,production["amount"]*2, 20)
+            simulation, self, production["name"], exchange, 0.08,production["amount"]*2, 6)
         self.craft = AutoProductionAgent(simulation, self)
         self.aquire = {}
 
         for k, v in production["prod"].items():
             a = Price_Believe_Aquire_Agent(
-                simulation, self, k, exchange, 0.2, 20)
+                simulation, self, k, exchange, 0.02, 6)
             a.set_target(v*2)
             a.set_price_max(10)
             self.aquire[k] = a

econ/cells/cell.py

@@ -24,7 +24,7 @@ class Cell:
     exchange: None
 
     def __init__(self,name,x,y,area,pop,demand,world) -> None:
-        pop=pop*100
+        pop=pop*10
         self.name=name
         self.loc_x=x
         self.loc_y=y

econ/simulation.py

@@ -86,12 +86,14 @@ class Simulation():
         Executes a tick of the simulation
         """
         start=time.time()
-
+        
+      
+       
+        self.tick_agents_random_order()
+        agentstep=time.time()
         for cell_id,c in self.cells.items():
             c.setup_demand_for_step(episode_length)
         setup=time.time()
-        self.tick_agents_random_order()
-        agentstep=time.time()
         for b in self.businesses:
             b.tick(self.tick_count)
             

main.py

@@ -28,8 +28,8 @@ cxs=[cx]
 # Create Demand
 #cx.submit_order(w,"Wood",0,1000,Side.BUY)
 #cx.submit_order(2,"Gem",1,10,Side.SELL)
-EPISODE_LEN=100
-NUM_EPISODES=50
+EPISODE_LEN=20
+NUM_EPISODES=20
 NUM_SEED_BUS=10
 
 
@@ -51,10 +51,8 @@ for a in tqdm(range(NUM_EPISODES)):
     print(f"|Stats| Num of Businesses: {len(sim.businesses)} Num Tickfunk: {len(sim.tick_funcs)} Time Agent Tick: {sim.timings['dsa']} Time Logging {sim.timings['dbl']}")
     sim.reset()
     for i in range(NUM_SEED_BUS):
-       sim.create_bussiness(1)
+        sim.create_bussiness(1)
 
-
-   
     
 
 log.writeEXData()

requirements.txt

@@ -2,4 +2,5 @@ lightmatchingengine
 pyyaml
 influxdb-client
 pandas
-sqlalchemy
+sqlalchemy
+tensorflow