Computational Intelligence and Neuroscience / 2017 / Article / Alg 1

Research Article

Joint Extraction of Entities and Relations Using Reinforcement Learning and Deep Learning

Algorithm 1

Training procedure for -Learning.
Initialize BILSTM, the Attention Layer, and Tree-LSTM with random parameters
Pre-train BILSTM, the Attention Layer, and Tree-LSTM respectively
for epoch = do
for each input sentence do
Use the deep learning models above to automatically extract features of , and generate and .
for = 1, 2 do
= the reward and state after taking the action
Perform gradient descent step:
The update rule is
Where is update step, and is the reward function (Section 3.1), and is the state-action pair of next time.
,
end for
end for
end for