Search Results for author:
Found 7 papers, 2 papers with code
Extrinsicaly Rewarded Soft Q Imitation Learning with Discriminator
In order to make this algorithm more robust to distribution shift, we propose more efficient and robust algorithm by adding to this method a reward function based on adversarial inverse reinforcement learning that rewards the agent for performing actions in status similar to the demo.
Staged Depthwise Correlation and Feature Fusion for Siamese Object Tracking
In this work, we propose a novel staged depthwise correlation and feature fusion network, named DCFFNet, to further optimize the feature extraction for visual tracking.
Discriminator Soft Actor Critic without Extrinsic Rewards
The methods based on reinforcement learning, such as inverse reinforcement learning and generative adversarial imitation learning (GAIL), can learn from only a few expert data.
Improving Minimal Gated Unit for Sequential Data
As a result of the experiment, the effectiveness of the proposed method was confirmed.
Random Projection in Neural Episodic Control
End-to-end deep reinforcement learning has enabled agents to learn with little preprocessing by humans.
Machine translation considering context information using Encoder-Decoder model
The paper propose a new model which can integrate context information and make translation.
Faster Deep Q-learning using Neural Episodic Control
The research on deep reinforcement learning which estimates Q-value by deep learning has been attracted the interest of researchers recently.
