Early Rumor Detection Based on Deep Recurrent Q-Learning

Algorithm 1

Training DRQN.

	Input: Network , Environment set , Experience pool
	Output:
(1)	Initialize current network , and target network ,
(2)	for each epoch do
(3)	Select an environment from
(4)	Initialize environment , and get state
(5)	while true do
(6)	According to , use -greedy strategy to select action from
(7)	Perform action in the environment to get the new state and reward
(8)	if is full do
(9)	Delete the oldest experience record
(10)	end if
(11)	Insert into
(12)
(13)	if is the last state do
(14)	break
(15)	end if
(16)	end while
(17)	if is full do
(18)	Select a batch of records from randomly
(19)	for each record do
(20)	Use target network to get
(21)	Use loss function to update current network
(22)	Update current network with target network every epochs
(23)	end for
(24)	end if
(25)	end for