Changing the way reward is given so that agent performs well.

train.py

@@ -11,33 +11,43 @@
 agent = Agent(window_size)
 data = getStockDataVec(stock_name)
 l = len(data) - 1
-batch_size = 32
+batch_size = 64
 
 for e in xrange(episode_count + 1):
 	print "Episode " + str(e) + "/" + str(episode_count)
 	state = getState(data, 0, window_size + 1)
 
 	total_profit = 0
 	agent.inventory = []
+	b=0
+	a=0
 
 	for t in xrange(l):
 		action = agent.act(state)
 
 		# sit
 		next_state = getState(data, t + 1, window_size + 1)
 		reward = 0
+		a+=1
 
 		if action == 1: # buy
 			agent.inventory.append(data[t])
 			print "Buy: " + formatPrice(data[t])
+			b=b+1
+			a=0
 
 		elif action == 2 and len(agent.inventory) > 0: # sell
 			bought_price = agent.inventory.pop(0)
-			reward = max(data[t] - bought_price, 0)
+			reward =(data[t] - bought_price)*100
 			total_profit += data[t] - bought_price
+			b=0
+			a=0
 			print "Sell: " + formatPrice(data[t]) + " | Profit: " + formatPrice(data[t] - bought_price)
 
+		if(b>10 or a>20):
+			reward+=-200
 		done = True if t == l - 1 else False
+
 		agent.memory.append((state, action, reward, next_state, done))
 		state = next_state