def run_pretrained(input_state,model,action_states,gameState):
print '\n\nLoading pretrained weights onto model...'
model.load_weights(p.PRETRAINED_PATH)
epsilon=1
while True:
print 'Running pretrained model (no exploration) with weights at ', p.PRETRAINED_PATH
nn_out = model.predict(input_state,batch_size=1,verbose=0)
nn_action = [[0,0]]
nn_action[0][np.argmax(nn_out)] =1
action,rand_flag = select_action(nn_action+action_states,prob=[epsilon,(1-epsilon)*1/7,(1-epsilon)*6/7])
rgbDisplay, reward, tState = gameState.frame_step(action)
grayDisplay = (np.dot(np.fliplr(imrotate(imresize(rgbDisplay, (80,80), interp='bilinear'), -90))[:,:,:3], [0.299, 0.587, 0.114])).reshape((1,1,80,80))
output_state = np.append(grayDisplay,input_state[:,:p.HISTORY-1,:,:], axis=1)
#############################################################################################################################################################################
flappy_double_dqn.py 文件源码
python
阅读 23
收藏 0
点赞 0
评论 0
评论列表
文章目录